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          ISL Colloquium        

We are witnessing a profusion of networked robotic platforms with distinct features and unique capabilities. To exploit the diversity of such robotic networks, we are contriving ecosystems of tightly interconnected and interdependent heterogeneous entities. However, as connections are established, information is shared, and dependencies are created, these systems give rise to new vulnerabilities and threats. I begin my talk by addressing the question of how heterogeneity affects the privacy of dynamic robot networks. With the ultimate goal of securing disruption-free operation, I introduce a model of differential privacy aimed at concealing critical robotic entities. Yet, even if we are able to protect individual robot roles, the hardware platforms may still be compromised. In light of this threat, my focus then shifts to the question of how to provide resilience in the face of non-cooperative and malicious agents. I show how precautionary connectivity management allows the robot networks to function, even in the presence of compromised individuals. Finally, I illustrate the effectiveness of this strategy on applications of vehicle flocking and perimeter surveillance.


 

The Information Systems Laboratory Colloquium (ISLC) is typically held in Packard 101 every Thursday at 4:15 pm during the academic year. Refreshments are usually served after the talk.

The Colloquium is organized by graduate students Martin Zhang, Huseyin Inan, Reza Takapoui, and Zhengyuan Zhou. To suggest speakers, please contact any of the students.


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author: cloud9791

Lunes nang umaga hindi na maalala ni Lisa kung paano sya nakatulog.
Gising na ang asawa at nakapaghanda na para pumasok. Nakapaghanda na rin ito nang almusal nilang dalawa. Isang ulirang asawa si Noel kaya nakonsenysa muli si Lisa at nagalaw sya nang iba bukod sa asawa nya.

Parang ayaw nya muna pumasok sa trabaho. Alam nyang makikita na naman nya ang kanyang Boss. Baka makakuha na naman ito ng tyempo maggamit sya muli.

Sa opisina nagkwentuhan silang magkaka officemate.

Tawanan sa mga nangyari sa Outing.

Si Beth ay tawa ng tawa dahil pag uwi daw nya sa bahay ay suka sya ng suka sa dami nang nainom.

si Lisa lang ang pangiti - ngiti. Minamasdan lang habang nagkekwentuhan ang mga kasama sa trabaho.

Sa isang sulok habang naglilinis minamasdan ni Mang Jay si Beth. Gandang-ganda sya kay Mam Lisa nya pero alam nyang type ito ng Boss nya.
Sunod kay Lisa ay type din nya ang batang-bata pang dalagang si Beth. Bagong graduate lang ito sa college at unang trabaho ang kumpanya ng Boss nya.

Cute ito at maumbok din ang suso at puwitan. Tigas titi din si Mang Jay kay beth. Sa isip nya matitikman din kita iha. Mag-intay ka lang at dyinggel lang ang pahinga mo sakin hehehe, sa isipan ng manyak ding janitor.

Dumating si Mr. Namero. Binati nang magandang umaga ang mga empleyada. Sabay pasimpleng himas sa kamay ni Lisa bago pumasok sa opisina nito.

Sa araw na yun, panay bisita sa kanya ni Mr. Namero at pag walang nakatingin ay pabulong - bulong ito sa tenga nya.
"Miss ko na ikaw baby, kelan uli tayo baby? bulong nito sa kanya.
Paminsan ay kinakagat kagat pa nito ang tenga nya at panay himas sa puwitan nya.

Nang malapit na ang uwian tinawag sya ni Mr. Namero sa opisina nito.

"Labas tayo baby, tayong dalawa lang miss na miss ko na ang baby ko"may halong malisyang sabi nito sa kanya.
“Miss ko na to agad”, sabay pahimas-himas sa may pwetan nya ipinasok ang kamay sa loob ng palda nya.

Di maintindihan ni Lisa ang Sarili, Nag-init si sya.
Alam nyang pag hindi sya umalis agad ay madadarang na naman sya sa boss nya. Ayaw man nya aminin pero parang nasasabik syang sumama sa Boss.
"" Hinihintay ako nang asawa ko sir, hindi ako pwedeng gabihin"
“Baka sa ibang araw lang na po sir"pagdadahilan ni Lisa pakawalan lang sya nang Boss nya.

Ok promise mo yan baby ha, tsaka di ba sinabi ko na sayong Love itawag mo sakin pag tayong 2 lang?"pagpapa aalala ni Namero.

Ok sir.. ay Love promise" napilitang sabihin ni Lisa.

Kinabukasan panay paalala sa kanya ng boss, buong maghapon sa opisina na lalabas sila mamaya.

Kung hindi sa text ay sa email nya may mga message ito sa kanya.
Puro kabastusan at kalaswaan ang mga ito.
Lumapit ito sa kanya at kinausap sya nang malapit na ang uwian.
"E kasi love hindi ko alam paano ako magpapa alam sa asawa ko " sabi ni Lisa sa Boss.
“Gusto mo ipaalam kita sa kanya?" madilim ang mata ni Namero habang nakatingin sa kanya.
Kinabahan si Lisa, baka mamamya ay ibuking pa sya nito sa mister.
"Mag-text ka sa mister mo may meeting tayo Honey" dagdag ng matanda.

"Ok Love"" sagot ni Lisa sa boss.
NAgtext nga si Lisa sa mister na baka gabihin ng uwi dahil may meeting ang kumpanya at mga empleyado.

Naintiindihan naman sya ni noel at pinag-ingat nalang umuwi ang asawa.
“Ok Honey ingat ka pauwi, Luv U"reply sa kanya ng mister.
Kumirot ang puso ni Lisa. Pero wala na sya maggawa.
MAgka holding hands pa sila nang matanda sa basement parking habang naglalakad patungo sa kotse nito.

Nalaman ni Lisa kung saan siya dadalhin ng Boss nya.
Sa isang Motel.

Hindi mapakali si Lisa. ngayon lang sya nakapasok sa isang motel. Ni minsan nung magsyota palang sila ni Noel ay hindi sya dinala ng asawa dito.

Napansin naman iyon ni Namero.
Inakbayan sya nito.
"Wag ka mag-alala Love 3hours lang tayo, para makauwi ka agad at hindi mag-alala mister mo”
"Pero gusto ko pag tayo ang magkasama ako lang ang iisipin mo at wala nang iba." Paalala nito sa kanya, sabay halik sa mga labi nya.

Magka-hawak kamay silang naglakad papunta sa kwarto nila. Inggit naman sa matanda ang Bellboy na naghatid sa kanila.

Wow swerte naman nito ni Sir"sa isip nito. Paano hindi nya maiisip na swerte ang matanda esobrang ganda at seksi ang ka -holding hands nito.
Sa tantiya nya sa itsura nang matanda, parang kalahati lang ata nang edad o sobra pa nga ang tantiya na ang tanda nito sa kasamang magandang babae. Tingin pati nya kay Lisa ay mukhang dalaga pa.

Matangkad ang matanda at hanggan balikat lang ang magandang dalaga. Kung titingnan ay para daddy na ito nang babae o baka nga Lolo pa! Sa pag-iisip ng bellboy.

Malaki ang tiyan nang lalaki pero mukhang malakas pa at direcho ang tindig. Nakasuklay nang maigi ang manipis nang buhok nito sa noo.

PAgpasok sa kwarto sa pwet na ni Lisa nakahawak ang si Mr. Namero.
PAgka- lock palang nang pinto, pinanggigilan na sya agad ng boss nya.
Napahiga sila sa kama ng motel habang naghahalikan. Nagpaubaya nalang si Lisa sa hayok na Boss. Sya man ay sabik na rin.
Ayaw man nya aminin, gusto nya mka-sex uli ang Boss nya. Hindi magkandatuto si Lisa sa kama. Paano, habang nagto-torrid kissing sila nang Boss niya ay sobrang likot ng mga kamay nito sa paghimas-lamas sa iba’t-ibang parte nang katawan nya.

Minsan ang isang kamay nito ay nasa may hiwa na ng pwet nya at nilalamas ang kanyang malambot na likuran. Ang isa naman ay nasa may mga suso nya.
Maya maya sa lilipat na naman ito sa umbok nyang namamasa na rin.
Nag-iinit na tuloy sa ginagawa ng Boss nya.

Mabilis din syang nahubaran ng boss nya. Sanay na sanay na eto pagdating sa babae. Namalayan na lang nya na naka underwear nalang sya.
PAti si Namero ay ilang segundo lang ay naka boxers shorts nalang ito. Tigas na tigas na ang ari nito.
Sumusungaw na sa ibabaw ng boxers shorts nito ang pinaka-ulo ng ari nito.
Sandaling tumayo at pinagmasdan ni Namero si Lisa habang nakahiga sa kama.
Luwang – luwa ang mga mata nya sa babaeng ngayon maangkin nya.
Kay ganda at nakakahalina nito habang naka underwear lang. Parang yung nakikita nyang nagagandahang mga model nang brochiere ng mga Sexy Lingerie.

Hinihintay ni Lisang muli syang roromansahin ng boss. Nabitin kasi sya at biglang tumigil ang boss nya. Pero nanatili lang ito nakatayo, habang hayok na pinagmamasdan sya.

""Baby stand up"utos nito sa empleyada, Tumayo ka dito sa may salamin.""
NAgtaka si Lisa pero sumunod agad eto sa utos ng Boss.
Kinuha ng Boss niya ang pinakabagong model ng celphone at biglang nagflash.

Kinukuhanan sya nito ng picture habang naka bra at panty nalang sya.

"" Love teteka, parang nakakahiya, wait lang sir "" pagtatakip ni Lisa sa katawan.
"" Psshst basta sumunod ka nalang, Akin lang naman tong mga picture na remembrance lang natin Baby. "
Habang panay ang click ng camera at flash ng ilaw ng celphone.
“Yan ganyan talikod" o yan sideview" pagbibigay ng instructions ng matanda.
"Ok Very Good Baby Girl, unting tuwad oh wow”
"Ganda talaga ng baby ko" si NAmero pa rin.

Nang makarami ibinaba na ng matanda ang celfone. Sandaling tiningnan ang mga kuha nya.
Magaganda ang mga kuha nyang picture ni Lisa.
Hindi na sya nakapagpigil at hinila ang magandang empleyada sa banyo.

Doon mabilis na hinubaran na sya ng matanda at sabay sila nag shower.
Nahihiya pa nung una si Lisa dahiil luwang-luwa ang mga mata ng Boss nya sa pagkaka titig sa hubad nyang katawan nya.
Pero nang simulan na nitong lamasin ang maseselang bahagi ng katawan nya ay natalo ng libog ang kanyang hiya at pagpigil.
Duong lamasin ng sabay ang dalawa nyang suso habang pumapatak ang shower.
Nasa likod nya ang boss nya habang nilalamas ng dalawang malalaking kamay nito ang ilalim ng kanyang boobs. Pagtapos ay kinabig nito ang kanyang ulo patagilid, sabay hayok na hinalikan sya sa mga labi.

Nagsumiksik ang dila nito sa mga labi nyang nakasara, kaya napanganga sya.
Nakapasok tuloy ang Mahabang dila nito sa loob ng bunganga nya.
Nasarapan dun si Lisa.
Gustong gusto nyo etong estilo nang pakikpaghalikan ng boss. Kapag silang mag-asawa ay lips to lips lang ang ginagawa sa kanya ng mister.
Pero etong sa boss nya ay halos umabot na ang dila nito sa kanyang lalamunan at ngala-ngala habang pagkiwal-kiwal ang ito sa loob ng bunganga nya. Nalulunok tuloy nya ang ibang laway nang Boss nya.

Maya ay nagsabunan naman sila ng mga katawan. Wala nang pagtutol si Lisa habang sinasabon ni Boss namero ang katawan nya. Kay sarap sa pakiramdam nya sa Dahan-dahang pagsabon sa kanya ng Boss.
Sinabon muna nito ang leeg nya. Isinunod nito ang tayung tayo nyang mga suso. Matagal ang pagsabon nito sa mga dede nya.
“ Aaayyyy sirr “ anas nang nasasarapang si Lisa.
PAgTapos sa kanyang puson, ang maumbok nyang pwetan naman ang sinabon nito, na lalong nagpataas sa pagnanasa ni Lisa.
Masuyo din nitong sinabon ang puke nya na natatabingan lang nga manipis na balahibo sa taas.
Sinamantala rin nitong kalabit-kalabitin ang tinggil nya at ang kanyang pussy lips.
Huuuunnnggghhhh, uuuuhhh sarapp naman nyan Love”

Habang sinasabon nya si Lisa, Napansin ni Boss Namero na Sinasabon din ni Lisa ang kanyang kahabaan.
Naka-tingin lang si Lisa sa kanyang alaga habang sinasabon ang kahabaan nito.
Taas - baba- taas baba ang malalambot netong mga kamay sa pagsabon sa kanyang. Sa pinaka-ulo, sa pinakapuno pabalik-balik lang.
Manghang – mangha si Lisa habang nakatitig sa Tigas na tigas na Ari ng Boss nya. MAs Mahaba ito at mataba kesa sa kanyang asawa.
" Sige lang Hon, sabunin mong maigi yan" O yung balls ko naman, yan ganyan" pagbibigay utos ni Namero sa kanya.
Sinabon din nya ang mga itlog nito. Lalo na ang ulo nito ay sinabon nyang maigi.

Maya ay nagbanlaw sa shower ang dalawa. Nang makapag banlaw, habang tuloy ang pagtagas ng tubig mula sa shower, biglang lumuhod ang matanda sa harap nya.
Sabay taas ng isang hita nya sa likod nito. Naramdaman na lang nya ang mga labi at dila ng matanda na lumapa sa mapag-paubaya nyang hiyas.

"Aaayyyy , aahhh Aayan sir aay ang galingg nyo sir, uhhmmmm"ungol ni lisa.

Matapos ang ilang minutong paglapa nito sa puki nya.
Tumayo ang boss nya sabay itinutok ang pinaka-ulo ng tarugo nito sa bukana ng hiyas nya.

"Here I come again baby!" I will fuck you! Are you ready baby?"hehe” may kabastusang sabi sa kanya ng matanda.

Sige Love, ipasok mo na" pagmamakaawa ni Lisa.
"" Hindi kitaa marinig baby, anong gusto mo?"" pambibitin ni Boss Namero.
"" Kantutin mo na ako Love Please.”
“O ayan sinabi ko na, yan ba gusto mo marinig?”,
“Wag mo na ako bitinin! "pasigaw na si Lisa. Nabigla rin sya sa sarili nya.

Ayun lang at unting unti ipinasok ng matanda ang kanyang kahabaan sa loob ni Lisa.
Sarap na sarap si Namero sa dahan-dahang pagpasok ng titi nya sa loob kiki ni Lisa.
Damang-dama nya ang padulas papasok nang Titi nya sa masikip, mainit at naglalawa nang kanal nito nang kaligayahan ng magandang empleyada.

“Oohhhhhhhhhhh” impit na ungol ni Lisa sa dahan-dahang paglusong nang mataba at mahabang kargada ng Boss.
Hanggang sa muling sumagad sa sinapupunan ni Lisa ang kahabaan ng boss.
“ooohhh… My Love ang sarapp naman nyan" wala sa isip na nasabi ni Lisa.
Tiningnan ni Lisa ang pagkakahugpong nila nang Boss nya.
Baun na baon ang 9 pulgadang titi nito sa kaloob-looban nya.
Ang nakikita nalang ni Lisa ay ang lapat na lapat nang kanilang mga umbok nang kani-kanilang mga bulbol.

Nagsimulang undayan sya ng kantot ng matanda patayo.
Malalim ang naabot nito sa kaloob-looban nya.
"oooohhhhhhh.. Aaaahhhhhhh sige pa Love.. ohhhhhhh ayan"" anas ni Lisa.
Nasusundot kasi nito ang kiliti sa kailaliman.
“Ang sarap mo Lisaa baby!” Si Boss Namero habang labas masok ang kahabaan sa puki nang magandang dilag.
“Ikaw na ang pinakamasarapp na puki na natikman ko.!"
Hakab na hakab nangg puki ni Lisa ang titi nya.
Bagay na bagay ang kani-kanilang mga ari para sa isa't isa.
Nagdedeliryo na sa sarap si Lisa.
Sa isip nya ay hindi na ata nya kayang mabuhay kung hindi matitikman ang Titi nang Boss nya.

“Aaahhhh shit! Love ayan na" si Lisa.
Biglang nanlambot ang mga tuhod ni Lisa.
Nilabasan na agad sya habang iilang minuto palang syang kinakantot ng Boss patayo.
Kung hindi sya hawak ng boss nya ay baka natumba sya sa loob ng banyo. Matapos nyang labasan ay binuhat sya ng boss nya na hindi nito binubunot ang ari nito sa loob nya.

Dinala sya nito sa kama nang magkahugpong pa rin ang mga ari nila. Dun pinagpatuloy ng boss Niya ang pagkantot sa kanya.

PArehas na nakasampay ngayon ang mga hita nya sa likod ng boss nya. Kitang kita nya tuloy kung panong lumusong ang matabang batuta ng boss nya sa puki nya.

Labas masok eto, walang pagod ang kanyang boss sa pagindayog sa ibabaw nya.
Biglang nawala ang mga itim sa mata ni Lisa nang igiling pa nang boss nya sa loob ng hiyas nya ang kahabaan nito.


"" Uuuhhmhmmmp shitt Aaahhhhhh.. uuunngggghhh aaaaahhhhhhh" Si Lisa habang imiikot ni Boss Namero ang puwetan sa ibabaw nya.
Gumigiling din ang ari ng boss nya sa kaloob-looban nya na lalong nagpabaliw kay Lisa.

""Im coming baby! Aaahhhh Youre so Good ! Baby aahhhh! I Love yourrr deliciousss pussyyy aahhhhhh" malakas na sabi ng matanda nang biglang labasan eto sa loob nya.

Sa lakas ng pagputok ng katas ng boss sa loob ng hiyas nya ay muli ring nilabasan si Lisa.
Damang dama nya ang bawat pagpuslit ng katas nito sa kaibuturan, dahil nakasagad pa ang kahabaan nito sa loob nya.
Hindi na naisip ni Lisa na maari syang mabuntis ng boss dahil sa ang pagsabog at direkta tumama sa loob ng sinapupunan nya ang katas ng Matanda.


itutuloy........


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Belum lama ini, Arbor Network melaporkan bahwa terdapat varian baru botnet yang telah berhasil menginfeksi malware ke lebih dari 25.000 komputer yang bersistem operasi Windows. Botnet ini mengggunakan metode yang belum diketahui caranya untuk menginfeksi korbannya. Hal yang pasti adalah, sekali terinfeksi, komputer korban akan dapat digunakan untuk menyebarkan botnet baru ini untuk menyerang sistem lain.


Apa itu Botnet??

Bagi yang belum tau apa itu botnet, botnet berasal dari kata robot network yaitu sekumpulan PC zombie yang sudah terinfeksi oleh virus malware dimana virus malware dikirimkan oleh seorang master botnet atau pengendali botnet yang bisa dibilang hacker karena telah menembus firewall dan masuk ke system komputer untuk menanamkan virus malware melalui internet. Ketika PC zombie atau PC yang sudah terinfeksi virus malware, maka master botnet dapat mengendalikan ribuan PC zombie melalui server PC C&C. C&C adalah Command and Control yaitu server komputer untuk memberi perintah dan dapat mengontrol ribuan PC zombie untuk penyerangan. Penyerangan bisa dengan DDOS attack, Spam message, dll. Tentu sangat mengerikan ketika seseorang berhasil mengendalikan Botnet ini, karena target sangat mudah ditaklukan, biasanya PC zombie digunakan untuk menyerang dengan DDOS untuk menyerang satu target oleh ribuan PC.


berikut adalah gambaran ketika master botnet melakukan penyerangan dengan C&C.


Peneliti dari Arbor Security Engineering & Response Team (ASERT), Matthew Bing, mengatakan bahwa Arbor ASERT telah melakukan pelacakan terhadap botnet yang biasa dipanggil dengan Fort Disco ini sejak bulan mei 2013. Mereka telah berhasil mengidentifikasi 6 situs command-and-control (C&C) yang mengendalikan lebih dari 25.000 mesin Windows yang terinfeksi botnet. Diklaim oleh mereka bahwa situs-situs pengendali itu kebanyakan berasal dari Rusia dan Ukraina. Setelah terinfeksi oleh Fort Disco, maka mesin Windows akan melakukan serangan brute force untuk menebak password dari suatu blog dan CMS yang menggunakan PHP. Sampai saat ini, diduga telah lebih dari 6.000 instalasi Joomla, WordPress dan Datalife Engine yang menjadi korban serangan bruteforce.

Pada kesempatan itu, Matthew Bing mengatakan bahwa pola serangan ini memiliki beberapa fitur canggih yang membuatnya mustahil untuk sepenuhnya dilacak. Tidak hanya itu, cara agar malware ini dapat ter-install di dalam sistem pun masih belum jelas. Dia dan timnya baru mampu menemukan nama asli dari malware ini yaitu “maykl_lyuis_bolshaya_igra_na_ponizhenie.exe”. Nama malware ini merujuk ke buku karangan Michael Lewis yang berjudul “The Big Short: Inside The Doomsday Machine” dalam bahasa Rusia yang di dalamnya terdapat executable attachment. Nama file lainnya yaitu, “proxycap_crack.exe” yang merujuk pada crack dari program ProxyCap.

Bing menambahkan bahwa masih belum diketahui motif dari pengumpulan password. Walaupun begitu, masalah pencurian password telah menjadi masalah serius bagi komunitas keamanan. Banyak kelompok yang menargetkan forum profesional telah tertangkap. Mereka berharap untuk dapat mencuri detail dari login pengguna yang akan digunakan untuk hal-hal berbahaya.


#IndonesiaCyberNews

          Internet Marketing Channels - Display        
I am devoting one blog entry to each major Internet Marketing Channel, this one is for Display advertising. People often ask what kind of internet Marketing I work with and I always say everything. Here's a list of what I consider most of everything followed by some definitions, color commentary, and general rule of thumb values for display advertising to help those that have not worked in the space much.

Internet Marketing Channels
- Display: CPM, CPC, CPA/Revenue/Profit Share
- Search: SEO, SEM
- Email: Paid, List Rental, Newsletters
- Affiliate: Internal and External programs
- Ad Networks

Display: Display mostly refers to purchasing banner ad space on third party internet sites. The site paying for the ad and resulting traffic is usually called the advertiser, and the site showing the ad to their visitors is the publisher. My rules of thumb are that well designed banners with compelling offers to reasonably qualified traffic should get about a 0.1% click-through rate (CTR). And well designed eCommerce sites with solid traffic (not junk) and a well-designed and optimized web site can see about a 5-10% conversion rate, with anything over 10% representing a pretty solid site and pretty solid traffic targeting. To me, there are three primary types of contract terms talked about for display deals. My diatribe on each follows with some commentary from both a publisher and advertiser perspective.

1) CPM - Cost per mil. This means an advertiser is paying a fixed amount for every 1,000 impressions of the ad on the publisher's site. Typical price ranges are from $1 to $10 but it varies widely depending on the demographics and intent of traffic. A wealthy demographic looking for information about helicopter tours in Hawaii might demand a very high CPM, but social media traffic that is not paying much attention to banners and is instead looking for ways to interact with their friends right now might demand a very low CPM. A $10 CPM or $10 effective CPM eCPM is considered pretty good, and anything higher than $10 is solid monetization. Realize that a $10 CPM is 1,000 cents / 1,000 impressions, so effectively that is a penny per impression.

Publishers on CPM deals: Normally, the ad impressions are recorded by both sides, on the publisher side they redirect the ad request so they can count requests and the advertisers count requests for the ad and track the referring url for the requests. Unfortuantely, unscrupulous advertisers take advantage of the ability to track visitors to publisher websites upon serving ads to them and they use the visit itself as behavioral targeting data which they then resell to other advertisers (acting as a publisher or simply a traffic data provider). If a deal sounds to good to be true, it probably is. Aside from behavioral retargeting, Publishers typically love CPM terms because it gives them guaranteed income regardless of the advertiser's capability to generate good banner ads or convert traffic. Also with CPM deals, publishers often have the flexibility to mix and match up their inventory as they can best sell it to reduce the amount of remnant or unused inventory they have and maximize the monetization of their traffic.

Advertisers on CPM deals: Advertisers typically dislike these terms because they feel like they can get burned if they are not paying attention. For instance, maybe other advertisers that paid higher CPM's get all of the good impressions from people likely to convert and you get stuck with the ones that are unlikely to ever convert like mobile phones, international traffic, traffic brought to the publisher site under false pretenses, unix or other useragents (browser and operating system types) which can not easily facilitate monetary transactions, or spiders, crawlers and bots which are not going to follow an ad tag link. Accordingly, advertisers will want to closely monitor the conversion of these ads, and have the ability to shut them off quickly before they have spent too much money if they are not performing well from an effective Cost per Action (eCPA) perspective. They may also want contracts that specify what times of day, exact site locations, browser types, etc the publishers can run impressions on. Brand advertisers whose products can not be easily purchased on the web (like frozen foods or pizza that one typically buys at the grocery store) may be less concerned about click through and conversion and happier with CPM deals than other types of advertisers.

2) CPC - cost per click. Each time a site visitor clicks on an ad, the advertiser must pay the publisher for the click. Becoming a de-facto standard as a compromise position for publishers and advertisers, largely due to google using CPC as their only method for search engine marketing and others following suit. Typical CPC costs are in the range of $0.25-$1.00, depending on the expected conversion rate and value of the conversion. Publishers willmontior effective CPM (eCPM) and advertisers will monitor effective CPA (eCPA) for CPC deals.

Publishers on CPC deals: Normally, the clicks are recorded by both sides using a redirect on the publisher side and referring url on the advertiser side. This is a compromise between CPM and CPA deals for all sides involved. The publisher needs to provide quality traffic for the ad impressions to get click-throughs, but it is incumbent on the advertiser to convert traffic directed to them. Publishers will monitor their eCPM (CPC price * average clicks per thousand impressions) for CPC deals because they want to ensure that they are monetizing their traffic as effectively as possible.

Advertisers on CPC deals: Advertisers are very concerned with conversion of CPC traffic. When the traffic arrives at their site, they have already paid for it, so any lost conversion is lost opportunity and turns the lead generation cost into sunk cost. Conversion should be carefully monitored from every source so that sources which convert well receive greater advertising expenditure while sources which do not convert at a profitable level are shut off. Unscrupulous publishers will try to find advertisers that do not carefully segment and measure conversion and marginal profitability so they can pile junk traffic to those sites. Advertisers also worry about click-fraud initiated both by the publisher and their agents and by the advertiser's competitors. There are many many well documented cases of people in low labor cost countries paid to erase all cookies then click on ads so that a publisher can bill for the clicks. Also, bots/http servers have been used plenty of times, even masking useragent values to make it difficult to tell it is a bot and increase CPC charges to advertisers. Finally, and especially for high cost high margin deals like helicopter tours in Hawaii and mortgages (historically) there are many cases documented where competitors click on your banner ads so that you incur the CPC charges but don't get any sales. There is further motivation to do this in SEM, but more on that later.

3) CPA/Revenue/Profit Share - Cost per Action. A publisher gets paid when they send traffic to an advertiser's site and that traffic performs some action on the advertiser's site, ie converts in some way. Variants include full revenue share where the publisher receives 10-90% of all the revenue received by the advertiser or similarly profit share. The publisher versus advertiser profit share rates depend on the margin of the product being sold by the advertiser and the leverage in the market of both the publisher and the advertiser. For eCommerce, CPA typically means purchasing something, and the action is recorded on the checkout page, often with the value of the transaction noted for revenue sharing calculations. But the 'A' can also be registering for a newsletter, installing software, and in the malware industry it can even mean installing a virus successfully on a machine and verifying that by having the virus phone home and demostrate control of the host machine. The CPA may be a fixed amount or it is frequently a percentage of the purchase amount on the other site. Typical CPA's are in the $2-$20 range, and vary widely depending on the value of the action to the advertiser and the conversion of traffic sent by the publisher. Viruses which turn host computers into zombies as parrt of bot networks garner about a $0.50 per machine payout.

Publishers on CPA deals: Publishers typically measure CPA by placing a cookie on a visitor's machine while they are on the publisher's site, then on the page on the advertiser's site after the action is complete, the Advertiser will place a call for a gif from the publisher's domain in the page so that the Publisher can read their domain cookie again and match it up to the referral. The gif is typically a 1x1 transparent pixel so the typical visitor does not even know that the publisher is monitoring their use of the site they were referred to. Typical CPA deals say that as long as the action is consummated within 7-30 days of the referral, the publisher will get their commission, so publishers get paid even if the action happens shortly after the initial click-through to the advertiser site. There are issues because this only works when cookies are accepted and able to persist. Historically this has been 95% of the time, but this is dropping as Firefox use is becoming more widespread, as Firefox has some nifty privacy plugins that allow cookies while you are on a site but erase them once you leave. Also, publishers will monitor their eCPM (average CPA payout * click-through rate * CPA conversion) for CPA deals because they want to ensure that they are monetizing their traffic as effectively as possible.

Advertisers on CPA deals: Advertisers generally like CPA deals as they can ensure that their advertising deals are marginally profitable and cash flow positive. The downsides are usually that publishers want to put a pixel on the conversion page of your site, and advertisers do not neccesarily want to share their conversion volume with every publisher whose site they run ads with. Also, since publishers may be paid up to as many as 30 days after the inital click-through to an advertiser site, it is possible that multiple publishers may try to claim a CPA fee for the same single conversion. Finally, the fact that someone converted on your site is behavioral data which third parties may use to try to target other offers at your site's traffic. Many of these problems can be avoided by building a 3rd party tracking system as I describe elsewhere on this blog, but most advertisers are either unaware or unwilling to pursue this option.

Which one?
Which of the above methods are used predominantly seems to swing with economic conditions. When times are good and advertising budgets are flowing, publishers can hold out for CPM deals, but when times are tight and advertising budgets are scarce and highly accounted for, the few advertisers out there with budgets still flowing can demand CPA deals. There are exceptions, of course, for highly valuable traffic and sites that convert exceptionally well, but generally the ebb and flow goes with the economic times.

At some point, I need to do a post on ad servers, which is the tool typically used for all of these display advertising methods and more. These high volume servers are typically built for speed and very high availability, and include all of the tracking that one desires for any of the methods listed above and more.
          Cracking AES/3-DES        

In 2002, a distributed network (desitributed.net) was successfully recovers a DES encryption key within 2.25 days. In order to estimate if 3-DES or AES keys can be recovered using a brute-force attack, this paper calculates the number of encryption operations and the (potentially) available processing power.
One of the largest distributed computing projects, folding@home estimates that with utilization of modern hardware such as Graphic Processing Unit (GPU), it is possible to achieve an acceleration of up to forty times (x40) over CPU due to its ability to perform “an enormous number of Floating Point OPerations (FLOPs) “ (Vijay Pande, 2010). Therefore, by using 200,000 actively processing computers, it is possible to surpass the 10 Petaflop level. As such, it is safe to assume that one average each participating machine contributes:




10×(10^15)÷200,000=50,000,000,000=50*(10^9)


or 50 billion calculations per second.
To amass the required computing power to brute force 3-DES or AES encryption, a bot network could be use to “harvest” idle CPU/GPU cycles. One of the most advance malware today, TDL-4, controls over 4.5 million infected computers in 2011 (Sergey Golovanov and Igor Soumenkov, 2011). Therefore, using previous assumption that zombie (infected computer) is capable of processing 50 billions calculations per seconds, the total computing power of a bot-net network such as TDL-4 is:




50*(10^9)*4.5*(10^6)=2.25×10^17=225×10^15


or 225 quadrillion (short scale) operations per second.
S. Kelly (2006) note that because in 3DES encryption scheme, the encryption keys relationship is C = E_k3(D_k2(E_k1(p))), in order to brute force a 3DES encryption a total of 2^168 cryptographic operation will be required. Assuming that a single 3DES decryption takes a microsecond (10^-6), it will take:



2^168÷225×10^15×10^6


1.66286409 × 10^27 second, or 5.26941088 × 10^19 years. This is far longer than the universe exist (4.339×10^17 seconds). The reader should note that the figure is by far smaller than what was estimated by S. Kelly (2006) and this is due to increased computing power of moder CPU and GPU devices. Regardless, it is safe to assume that 3DES can withstand a brute force attack.

Bibliography

  • Kaur, G, & Kumar, D 2010, 'Performance and Analysis of AES, DES and Triple DES against Brute Force Attack to protect MPLS Network', International Journal Of Advanced Research In Computer Science, 1, 4, p. 420, EDS Foundation Index, EBSCOhost, viewed 17 March 2012.
  • Ross J. Anderson 2008, “Security Engineering: A Guide to Building Dependable Distributed Systems”. 2nd Edition. Wiley.
  • Sergey Golovanov, Igor Soumenkov 2011, “TDL4 – Top Bot” [online]. Kaspersky Lab ZAO. Available from: http://www.securelist.com/en/analysis/204792180/TDL4_Top_Bot?print_mode=1 (accessed: March 17, 2012).
  • S. Kelly, 2006, “Security Implications of Using the Data Encryption Standard (DES)” [online]. Network Working Group. Available from: http://www.ietf.org/rfc/rfc4772.txt (accessed: March 17, 2012).
  • Vijay Pande, 2010. “Folding@home high performance client FAQ” [online]. Available from: http://folding.stanford.edu/English/FAQ-highperformance (accessed: March 17, 2012).

          Bot Net Angriffe auf WordPress und Joomla        
Zur Zeit gibt es vermehrt Angriffe auf lokale Installationen von WordPress und Joomla Weltweit wurde eine stark überhöhte Anzahl an ...
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          Introducing Threat Operations: TO in Action        

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As we wrap up our Introduction to Threat Operations series, let’s recap. We started by discussing why the way threats are handled hasn’t yielded the results the industry needs and how to think differently. Then we delved into what’s really required to keep pace with increasingly sophisticated adversaries: accelerating the human. To wrap up let’s use these concepts in a scenario to make them more tangible.

We’ll tell the story of a high-tech component manufacturer named ComponentCo. Yes, we’ve been working overtime on creative naming. ComponentCo (CCo) makes products that go into the leading smartphone platform, making their intellectual property a huge target of interest to a variety of adversaries with different motives.

  • Competitors: Given CCo’s presence inside a platform that sells hundreds of millions of units a year, the competition is keenly trying to close the technology gap. A design win is worth hundreds of millions in revenue, so it’s not above these companies to gain parity any way they can.
  • Stock manipulators: Confidential information about new products and imminent design wins is gold to unscrupulous traders. But that’s not the only interesting information. If they can see manufacturing plans or unit projections, they will gain insight into device sales, opening up another avenue to profit from non-public information.
  • Nation-states: Many people claim nation-states hack to aid their own companies. That is likely true, but just as attractive is the opportunity to backdoor hundreds of millions of devices by manipulating their underlying components.

ComponentCo already invests heavily in security. They monitor critical network segments. They capture packets in the DMZ and data center. They have a solid incident response process. Given the money at stake, they have pretty much every new, shiny object that promises to detect advanced attackers. But they are not naive. They are very clear about how vulnerable they are, mostly due to the sophistication of the various adversaries they face.

As with many organizations, fielding a talented team to execute on their security program is challenging. There is a high-level CISO, as well as enough funding to maintain a team of dozens of security practitioners. But it’s not enough. So CCo is building a farm team. They recruit experienced professionals, but also high-potential system administrators from other parts of the business who they train in security. Bringing on less experienced folks has had mixed results – some of them have been able to figure it out, but others haven’t… as they expected when they started the farm team. They want to provide a more consistent training and job experience for these junior folks.

Given that backdrop, what should ComponentCo do? They understand the need to think differently about attacks, and how important it is to move past a tactical view of threats to see the threat operation more broadly. They understand this way of looking at threats will help existing staff reach their potential, and more effectively protect information. This is what that looks like.

Harness Threat Intel

The first step in moving to a threat operations mindset is to make better use of threat intelligence, which starts with understanding adversaries. As described above, CCo contends with a variety of adversaries – including competitors, financially motivated hackers, and nation-states. That’s a wide array of threats, so CCo decided to purchase a number of threat feeds, each specializing in a different aspect of adversary activities.

To leverage external threat data they aggregate it all into a platform built to reduce, normalize, and provide context. They looked at pumping the data directly into their SIEM, but at this time the flood of external data would have overwhelmed the existing SIEM. So they need yet another product to handle external threat data.

They use their TI platform to alert based on knowledge of adversaries and likely attacks. But these alerts are not smoking guns – each is only the first step in a threat validation process which sends the alert back to the SIEM looking for supporting evidence of an actual attack. Given their confidence in this threat data, alerts from these sources have higher priority because they match known real-world attacks.

Given what is at stake for CCo, they don’t want to miss anything. So they also integrate TI into some of their active controls – notably egress filters, IPS, and endpoint protection. This way they can quarantine devices communicating with known malicious sites or otherwise indicating a compromise before data is lost.

Enrich Alerts

We mentioned how an alert coming from the TI platform can be pushed to the SIEM for further investigation. But that’s only part of the story. The connection between SIEM and TI platform should be bidirectional, so when the SIEM fires an alert, information is pulled from the TI platform which corresponds to the adversary and attack.

In case of an attack on CCo, an alert involving network reconnaissance, brute force password attacks, and finally privilege escalation would clearly indicate an active threat actor. So it would be helpful for the analyst performing initial validation to have access to all the IP addresses the potentially compromised device communicated with over the past week. These addresses may point to a specific bot network, and can provide a good clue to the most likely adversary. Of course it could be a false flag, but it still provides the analyst a head start when digging into the alert.

Additional information useful to an analyst includes known indicators used by this adversary. This information helps to understand how an actor typically operates, and their likely next step. You can also save manual work by including network telemetry to/from the device for clues to whether the adversary has moved deeper into the network. Using destination network addresses you can also have a vulnerability scanner assess other targets to give the analyst what they need to quickly determine if any other devices have been compromised.

Finally, given the indicators seen on the first detected device, internal security data could be mined to look for other instances of that attack regardless of whether network traffic shows the device acting strangely. Then the analyst can tell whether the attacker has been successful using the same tactic to establish other footholds in the environment. This is critical when it’s time to eradicate an adversary.

This is pretty simple stuff which any semi-experienced analyst does as he/she validates an attack and assesses potential damage. The difference is all this data can be pulled automatically before an alert reaches the analyst. By the time an analyst starts to dig in, they shouldn’t have to start with a bunch of manual digging to get everything they need to investigate. They start validation in a good position to quickly understand what happened and assess the blast radius of the compromise.

Building Trustable Automation

Automation within threat operations can mean a lot of things. Assembling all the supporting information an analyst needs for threat validation prior to starting the process is clearly automation. But let’s move a little deeper into specific actions which can occur automatically. As described above, ComponentCo has a pretty mature response capability and typically removes all potentially compromised device from the network at the beginning of response to limit possible damage.

But this impacts response in multiple ways. First, it may tip off the adversary, prompting them to burrow deeper and find other points of entry. Additionally, CCo loses their opportunity to monitor adversary activity to figure out what they were trying to do and how.

Automation can help. CCo can automatically move a suspicious device onto a VLAN where all network traffic is captured, which won’t tip off the adversary to their discovery. They also start to pull EDR telemetry off the device at least every 30 minutes, to ensure data is captured even if the adversary is tampering with endpoint’s logs. This provides opportunity to see what adversaries are up to, and perhaps to establish preemptive workarounds in anticipation of the attacker’s next move.

Another step CCo may add to their response playbook is to automatically update a network blacklist with any unknown external networks a compromised device has been communicating with, under the assumption they are likely botnets, and block traffic to them. They can search their network and device security data for other devices connecting to those networks, which can help identify additional compromised devices.

Workflow and Process Automation

Underlying all these functions is an automate first mentality, where the team builds playbooks which specify actions to take in response to typical threats. This is valuable for several reasons, including consistent response and minimization of human error. But scaling the security team is the most important. CCo is a very desirable place to work, and doesn’t generally have an issue finding talented folks, but skilled security staff are still in high demand. By combining a threat operations mindset with a heavy dose of automation, CCo can make less sophisticated (and cheaper) analysts more productive.

Of course they still use Tier 3 analysts to handle tough and complicated incidents. But for others their playbooks can guide Tier 1 & 2 analysts. Let’s use an example of a response playbook for a phishing issue leads off a targeted attack.

In our scenario a junior staffer in Finance received a phishing email claiming to come from his bank, and requiring immediate attention. The employee fell for the ruse and clicked the link, which compromised his device. The compromised device began internal reconnaissance and connected to a known botnet. At that point an alert triggered and the automated playbook kicked in, putting the device in a fully logged VLAN and increasing the monitoring level, then updating egress filters and the IPS configuration to watch for indicators corresponding to the initial attack. A full image of the device was taken prior to clean-up, and then it was restored and resumed normal operations quickly, without any real data loss or extensive manual effort.

But given the sophistication of its adversaries, CCo doesn’t assume any phishing attack is just everyday phishing. So they install the image of the compromised device in a sandbox to see what it does. This secondary analysis shows the phishing attack was a diversion. A secondary malware kit activated the next day, which had all of the earmarks of far more sophisticated nation-state malware.

So this gets immediately escalated to Tier 3.

Handling a Targeted Threat

Escalation of what appears to be a nation-state level attack triggers yet another playbook, which triggers the threat intel and alert enrichment functions discussed previously. By the time the case reaches a Tier 3 responder, they will quickly understand the adversary, their tactics, and where else similar attacks have been seen – inside or outside CCo.

At this point the response team knows they are under real attack bt a sophisticated adversary, and automatically starts capturing egress traffic and locking down their most critical assets as a precaution. Because related information has already been collected and associated with this case, the Tier 3 analyst can very quickly figure out the adversary’s TTPs and choose an appropriate response.

Obviously there is a lot more effort and detail to actually eradicate a nation-state from CCo’s systems, but they have a response process and playbook for that. The point to highlight here is that what looked like simple phishing, handled in a largely automated fashion, uncovered a sophisticated nation-state campaign. At that point the threat operations mindset enables CCo to seamlessly escalate and provides a Tier 3 analyst with all available information to streamline attack and adversary research, and accelerate both damage assessment and eventual eradication of the adversary.

So what is required for this threat operations mindset?

  1. Define processes and playbooks: Consistent activity requires initial work to figure out appropriate responses for a number of different scenarios. The evolution always starts by defining how you want the team to behave, and then working to implement consistent processes.
  2. Implement an external threat data aggregation platform: External threat data is key to understanding what adversary you are facing and what they are likely to do. Numerous feeds are available, but to avoid overload and ensure can effectively utilize the data, you’ll want to aggregate and process it for better context.
  3. Integrate external and internal security data with analytics: Once aggregated, the external data needs to be analyzed alongside internal security data to pinpoint potential issues and identify patterns of malicious behavior based on what’s happening in the wild. At this point you get much more relevant alerts, enriched with supporting information about probable adversaries and indications of whether an attack has spread within your environment.
  4. Orchestrate existing monitors and controls: The key to operationalizing a playbook is to have all the systems work together. So your TI aggregation platform (if a separate technology) needs a bi-directional connection to and from your SIEM. It can also send data to IPS devices and egress filters to block known bad sites. It can check with an advanced endpoint tool to confirm that what is reported from the network actually happened on the endpoint, and vice-versa.
  5. Automate first: Finally, given all this analysis and integration, trusted automation can block traffic to known bad sites and move compromised devices into quarantine networks or capture telemetry on detection of suspicious activity. Basically, if something can be documented in a playbook, you should be able to automate much of the process.

The end result is an orchestrated and automated ability to handle threats, equipping human analysts to do what they do best: pull on threads and make connections between isolated attacks which may represent sophisticated campaigns. Machines don’t do this well or automatically. If it can be enumerated in a playbook, it likely should be automated. If not it remains the purview of humans on the security team, and you can make them more productive by automatically aggregating the data they need to understand and address each situation.

With that we wrap up our Threat Operations series. We’re always interested in feedback on our research, especially our scenarios. Just drop us an email, tweet, or comment on this post – we’re happy to discuss.

- Mike Rothman (2) Comments Subscribe to our daily email digest
          Amazon Buys Robot Maker Kiva Systems for $775 Million        

Earlier this week, Amazon.com announced it was following through on plans to acquire Kiva Systems, Inc., a maker of robots and robotic platforms used in warehouses and shipping operations. Terms of the agreement indicate that Amazon will acquire all shares of Kiva for approximately $775 million in cash, and the deal is slated to close in Q2.

a_com_logo_RGB.jpgDave Clark, Amazon.com’s vice president, global customer fulfillment, pointed to the fact that Kiva shares Amazon’s passion for invention as a key ingredient to the new partnership. “Amazon has long used automation in its fulfillment centers, and Kiva’s technology is another way to improve productivity by bringing the products directly to employees to pick, pack and stow,” he said.

“For the past ten years, the Kiva team has been focused on creating innovative material handling technologies,” said Mick Mountz, CEO and founder of Kiva Systems. “I’m delighted that Amazon is supporting our growth so that we can provide even more valuable solutions in the coming years.”

Kiva Systems’ headquarters will remain in North Reading, Massachusetts.

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              TI, iRobot Announce Tech Partnership        

    Texas Instruments and iRobot Corp. announced a partnership today, whereby the latter will develop robotic technologies atop the former’s smart multicore OMAP platform.

    According to an official press release hailing the news, OMAP is a:

    …high-performing, ultra-power-efficient system-on-chip (SOC) that’s smaller than a dime… and …the platform’s smart multicore architecture sends processing tasks to cores and engines that can best do the job using the least amount of power possible.

    Texas Instruments provides several advanced features on the platform, such as sophisticated image and video accelerators.

    Last week TI updated its business outlook for the first quarter of 2012, narrowing and lowering its expected ranges for revenue and earnings per share (EPS). The company pointed to lower demand for Wireless products as the reason.

    According to TI, they currently expect financial results to be within the following ranges:

    Revenue: $2.99 – 3.11 billion compared with the prior range of $3.02 – 3.28 billion

    EPS: $0.15 – 0.19 compared with the prior range of $0.16 – 0.24.

    iRobot has delivered over 4,500 combat proven robots to military and civil defense forces worldwide. The company has also sold over 7.5 million home robots including the popular Roomba and Scooba models.

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              iRobot Nets Order for FirstLook Robots        

    iRobot Corp. announced a $1.5 million order for more than 100 of the company’s model 110 FirstLook robots. The order was funded by the Joint Improvised Explosive Device Defeat Organization (JIEDDO).

    Last April, we described the FirstLook as an unmanned ground vehicle (UGV) designed to assist its operator with observation and investigation of confined spaces.

    According to iRobot, the device is ideal for a wide range of infantry and special operations missions, including building clearing, raids and other close-in scenarios.

    iRobot 110 FirstLook 1.JPGThe lightweight “throwable” robot features four built-in cameras, two-way audio communication, and digital mesh networking capabilities, which would allow multiple units to relay radio communications signals. The 110 FirstLook is designed to withstand up to 15-foot drops onto concrete and is waterproof to three feet.

    The robot is designed to climb steps, overcome obstacles, turn in place and can right itself if it gets flipped over. It weighs less than five pounds.

    Tim Trainer, interim general manager of iRobot’s Military Robots business unit is excited by the positive feedback from customers who are trialing the FirstLook.

    “Similar to how iRobot’s PackBot and SUGV robots changed the way explosive ordnance disposal missions are conducted, we feel FirstLook will change how infantry and special operations missions are performed in the years ahead,” he said.

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              iRobot Secures 100th Patent        

    Answer: U.S. patent (U.S. 8,108,092)

    Question: What is iRobot’s 100th patent, Alex?

    Correct!

    Bedford, Mass.-based iRobot Corp. has hit the century mark in terms of patents, a milestone, which it describes as “an important attainment reflecting the company's ongoing attention to building strategic intellectual property.”

    The robot-maker’s 100th U.S. patent protects robotic ‘retrotraverse’ technology, which gives the firm’s iRobot 510 PackBot with User Assist Package (UAP) the ability to autonomously come back to its handler should the wireless communications link between operator and machine be dropped.

    iRobot_logo_black.jpgAccording to a company news release, the retrotraverse technology can be applied to networked and wireless robots in military, commercial, healthcare and household applications.

    Apparently the good folks at the patent office were quite busy with robot related submissions, as on the same day iRobot was awarded the patent for ‘retrotraverse’, it was also awarded a patent covering sonar technologies for robotic telepresence. The application of this particular technology can be seen in the company’s iRobot Ava mobile robotics offering, a platform that was developed to help robot designers, application developers and other specialists design cutting edge, affordable mobile robotic solutions.

    iRobot also holds 108 foreign patents and continues to pursue more than 250 patent applications pending worldwide.

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              Bluefin Robotics to Jointly Develop UUV        

    Two companies are joining forces to develop a novel, next-generation submersible that will answer the US Navy’s call to come up with a solution featuring increased mission time, operational range and payload carrying capacity.

    Battelle subsidiary Bluefin Robotics, which designs and manufactures Unmanned Underwater Vehicles (UUVs) and related technology, and The Columbia Group, a specialist with expertise in military undersea vehicles, diving systems, and shipboard launch and recovery systems have teamed up to deliver a dual-mode (manned and autonomous) vehicle currently named Proteus.

    Proteus (Small).jpgThe Columbia Group currently is developing the hull mechanical and electrical systems for the project, and Bluefin is supplying advanced autonomy technology for use in unmanned missions. Bluefin will also contribute mission planning capabilities and the power solution. Battelle is providing battery charging and systems integration support.

    David P. Kelly, President and CEO of Bluefin Robotics, is a firm believer in the partnership approach to solving this particular design challenge. “By combining the strengths of our organizations, we can field a vehicle that will meet the Navy’s needs and take UUV capabilities to the next level,” Kelly said.

    Proteus is 25-feet long, weighs 6,200 pounds and has up to 400 pounds of lift capability. Developers plan to hold an at-sea demonstration in the coming months.

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              ReconRobotics Wins Contract from US Army        

    ReconRobotics, Inc., has been awarded a $13.9 million contract for over 1,000 of its Recon Scout XT micro-robot kits from the U.S. Army. This is the largest order in the company’s history and, in terms of the number of units, it is also the largest micro-robot order ever issued by the U.S. Army ReconRobotics plans to complete deliveries on these orders by May 31, 2012.

    Recon_Scout_XT_Front_Infrared_Lights.jpg“We are honored that the U.S. Army has once again chosen our Recon Scout XT system for their dismounted troops,” said Ernest Langdon, Director of Military Programs for ReconRobotics. “Although these 1.2-lb robots are exceptionally small, they will play a big role in providing our warfighters with increased situational awareness and standoff distance as they conduct operations in active combat theaters.”

    ReconRobotics, which was formed to commercialize robotics technology developed at the University of Minnesota Distributed Robotics Lab, is no stranger to dealing with the US Army. Over the last six months, the company has received orders for 1,800 Recon Scout XT kits.

    The lightweight, throwable robot is well-suited for use by military and police. When used as directed, the robots provide operators with situational awareness and the ability to maintain a greater standoff distance between the user and the adversary.

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              iRobot Announces Record Results        

    Apparently Roomba business is good business. iRobot Corp. has announced its financial results for Q4 and for the full year ended December 31, 2011 and the news is positive. In fact, it was a record year for the Bedford-Mass.-based robotics manufacturer.

    According to an official company release:

    iRobot_logo_black.jpgRevenue for the fourth quarter of 2011 increased 15 percent to $130.8 million, compared with $114.0 million for the same quarter one year ago. Revenue for the full year 2011 increased 16 percent to $465.5 million from $401.0 million for the full year 2010.

    Net income in the fourth quarter of 2011 was $10.6 million, compared with $7.0 million in the fourth quarter of 2010. Net income for the full year 2011 was $40.2 million, compared with $25.5 million for the same period in 2010.

    “Our record financial results in 2011 were exceptional on all fronts, driven by especially strong performance in our Home Robots division,” said Colin Angle, chairman and chief executive officer of iRobot.

    Angle was very pleased with the home robot business, but cautioned that limited visibility in the defense business may lead to a decline in top and bottom line in the company’s G&I division.

    However, Angle said that iRobot plans to continue to make investments in marketing and research/development to maintain and increase the company’s market position.

    “To capitalize on our growing home robot business, intermediate and longer term opportunities in the defense business and exciting emerging opportunities, we will continue to make investments in marketing and R&D that extend our leadership position,” he said.

    Some highlights from the release:

    • Strong demand in overseas markets drove a 21 percent year-over-year increase in full-year home robot revenue.
    • International home robot revenue of $196 million comprised 70 percent of total home robot 2011 revenue.
    • Government & industrial robot revenue grew 9 percent in 2011, driven by shipments of Small Unmanned Ground Vehicles and spares.
    • In 2011, operating cash flow was $55.7 million, compared with $49.2 million in 2010. As a result of improved net income, iRobot’s year-end cash and investment position was $184 million.

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              Insights        

    Anomaly Detection What The Anomaly Detection Tool detects and filters out suspicious clicks. These suspicious clicks are recognized when there are many clicks on relatively few impressions. Suspicious clicks might be generated through: bot nets advertisers’ competitors crawlers hosting providers anti-virus software browser verifying ad links apps verifying ad links testing campaigns, landing page or […]

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              Cyberpunk Radio - #118 - Botnets        
    Bot net operatives have taken control of almost 12 million new IP addresses since January. The United States has the largest number of bot net-controlled machines, with 18 percent of the world total. The number of new zombie machines represents a 50 percent rise over last year. Researchers attribute the explosion to bot net controllers trying to wrestle complete control of the Internet. A computer worm is a self-replicating computer program- painting the Net in shades of crimson and green; fade to grey. It uses the Network to send copies of itself to other computers on the Network. Worms get code updates periodically, making them nearly impossible to disrupt. Infected machines query for updated commands through encrypted p2p networks- the Darknets. It appears the latest variant of Worms are part of a coordinated, distributed bot net of historic proportion. If the number of infected machines controlled by the bot net proceeds to increase at the current exponential rate, nearly 1/3 of all computers connected to the Internet will be infected by the end of next year. Authorities claim the true purpose of this ubiquitous bot net remains a mystery. Until recently the bot net has been essentially dormant, reticent of purpose. Deep packet NSA intercepts from Darknet, decoded via MAGISTRAND using parallel SILKWORTH supercomputer systems, hint at the nefarious goals of the Bot Net; encrypted data streams used by the botnet take time to decipher- weeks at a minimum, even for the NSA. This results in a equivalent time shift from the time stamp on the intercepted data. This much is known. Recruitment of human agents into various Darknet Factions appears to well under way. It appears that some select Massively Multiplayer Online Role playing (MMOR) and First person shooter (FPS) computer games contain "back doors" that allow redirects from local (user) and game company servers to a slew of encrypted p2p Darknet network servers located in such far flung locations as North Korea, Russia, China, Pakistan, and Brazil. IP addresses of these servers is changed through encrypted updates, making disruption impossible; a new, anarchistic government- DarkNet. In this Darknet, much like in video games, level up achievements are awarded for outstanding performance. However, unlike in video games, achievement awards are based on real world actions- such as new member recruitment, development of underground operations involved in subversive or 'criminal' activity. A recently arrested member of a particularly notorious Darknet Faction, believed to be involved in sex worker trafficking and drug distribution, bragged of assets including control of networks in major banking and infrastructure centers, as well as military command and control networks. It is rumored that the reported "accidental" launch of a trident missile last month was a direct result of this Factions' intrusion into a previously secure NET COM systems.

                      
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              Bejtlich Books Explained        
    A reader asked me to explain the differences between two of my books. I decided to write a public response.

    If you visit the TaoSecurity Books page, you will see two different types of books. The first type involves books which list me as author or co-author. The second involves books to which I have contributed a chapter, section, or foreword.

    This post will only discuss books which list me as author or co-author.

    In July 2004 I published The Tao of Network Security Monitoring: Beyond Intrusion Detection. This book was the result of everything I had learned since 1997-98 regarding detecting and responding to intruders, primarily using network-centric means. It is the most complete examination of NSM philosophy available. I am particularly happy with the NSM history appendix. It cites and summarizes influential computer security papers over the four decade history of NSM to that point.

    The main problem with the Tao is that certain details of specific software versions are very outdated. Established software like Tcpdump, Argus, and Sguil function much the same way, and the core NSM data types remain timeless. You would not be able to use the Bro chapter with modern Bro versions, for example. Still, I recommend anyone serious about NSM read the Tao.

    The introduction describes the Tao using these words:

    Part I offers an introduction to Network Security Monitoring, an operational framework for the collection, analysis, and escalation of indications and warnings (I&W) to detect and respond to intrusions.   Part I begins with an analysis of the terms and theory held by NSM practitioners.  The first chapter discusses the security process and defines words like security, risk, and threat.  It also makes assumptions about the intruder and his prey that set the stage for NSM operations.  The second chapter addresses NSM directly, explaining why NSM is not implemented by modern NIDS' alone.  The third chapter focuses on deployment considerations, such as how to access traffic using hubs, taps, SPAN ports, or inline devices.  

    Part II begins an exploration of the NSM “product, process, people” triad.  Chapter 4 is a case study called the “reference intrusion model.”  This is an incident explained from the point of view of an omniscient observer.  During this intrusion, the victim collected full content data in two locations.  We will use those two trace files while explaining the tools discussed in Part II.  Following the reference intrusion model, I devote chapters to each of the four types of data which must be collected to perform network security monitoring – full content, session, statistical, and alert data.  Each chapter describes open source tools tested on the FreeBSD operating system and available on other UNIX derivatives.  Part II also includes a look at tools to manipulate and modify traffic.  Featured in Part II are little-discussed NIDS' like Bro and Prelude, and the first true open source NSM suite, Sguil.

    Part III continues the NSM triad by discussing processes.  If analysts don’t know how to handle events, they’re likely to ignore them.  I provide best practices in one chapter, and follow with a second chapter explicitly for technical managers.  That material explains how to conduct emergency NSM in an incident response scenario, how to evaluate monitoring vendors, and how to deploy a NSM architecture.

    Part IV is intended for analysts and their supervisors.  Entry level and intermediate analysts frequently wonder how to move to the next level of their profession.  I offer some guidance for the five topics with which a security professional should be proficient: weapons and tactics, telecommunications, system administration, scripting and programming, and management and policy.  The next three chapters offer case studies, showing analysts how to apply NSM principles to intrusions and related scenarios.

    Part V is the offensive counterpart to the defensive aspects of Parts II, III, and IV.  I discuss how to attack products, processes, and people.  The first chapter examines tools to generate arbitrary packets, manipulate traffic, conduct reconnaissance, and exploit flaws inn Cisco, Solaris, and Microsoft targets.  In a second chapter I rely on my experience performing detection and response to show how intruders attack the mindset and procedures upon which analysts rely.

    An epilogue on the future of NSM follows Part V.  The appendices feature several TCP/IP protocol header charts and explanations.   I also wrote an intellectual history of network security, with abstracts of some of the most important papers written during the last twenty-five years.  Please take the time to at least skim this appendix,  You'll see that many of the “revolutionary ideas” heralded in the press were in some cases proposed decades ago.

    The Tao lists as 832 pages. I planned to write 10 more chapters, but my publisher and I realized that we needed to get the Tao out the door. ("Real artists ship.") I wanted to address ways to watch traffic leaving the enterprise in order to identify intruders, rather than concentrating on inbound traffic, as was popular in the 1990s and 2000s. Therefore, I wrote Extrusion Detection: Security Monitoring for Internal Intrusions.

    I've called the Tao "the Constitution" and Extrusion "the Bill of Rights." These two books were written in 2004-2005, so they are tightly coupled in terms of language and methodology. Because Extrusion is tied more closely with data types, and less with specific software, I think it has aged better in this respect.

    The introduction describes Extrusion using these words:

    Part I mixes theory with architectural considerations.  Chapter 1 is a recap of the major theories, tools, and techniques from The Tao.  It is important for readers to understand that NSM has a specific technical meaning and that NSM is not the same process as intrusion detection.  Chapter 2 describes the architectural requirements for designing a network best suited to control, detect, and respond to intrusions.  Because this chapter is not written with specific tools in mind, security architects can implement their desired solutions regardless of the remainder of the book.  Chapter 3 explains the theory of extrusion detection and sets the stage for the remainder of the book.  Chapter 4 describes how to gain visibility to internal traffic.  Part I concludes with Chapter 5, original material by Ken Meyers explaining how internal network design can enhance the control and detection of internal threats.

    Part II is aimed at security analysts and operators; it is traffic-oriented and requires basic understanding of TCP/IP and packet analysis.  Chapter 6 offers a method of dissecting session and full content data to unearth unauthorized activity.  Chapter 7 offers guidance on responding to intrusions, from a network-centric perspective.  Chapter 8 concludes part III by demonstrating principles of network forensics.

    Part III collects case studies of interest to all types of security professionals.  Chapter 9 applies the lessons of Chapter 6 and explains how an internal bot net was discovered using Traffic Threat Assessment.  Chapter 10 features analysis of IRC bot nets, contributed by LURHQ analyst Michael Heiser. 

    An epilogue points to future developments.  The first appendix, Appendix A, describes how to install Argus and NetFlow collection tools to capture session data.  Appendix B explains how to install a minimal Snort deployment in an emergency.  Appendix C, by Tenable Network Security founder Ron Gula, examines the variety of host and vulnerability enumeration techniques available in commercial and open source tools.  The book concludes with Appendix D, where Red Cliff Consulting expert Rohyt Belani offers guidance on internal host enumeration using open source tools.

    At the same time I was writing Tao and Extrusion, I was collaborating with my friends and colleagues Keith Jones and Curtis Rose on a third book, Real Digital Forensics: Computer Security and Incident Response. This was a ground-breaking effort, published in October 2005. What made this book so interesting is that Keith, Curtis and I created workstations running live software, compromised each one, and then provided forensic evidence for readers on a companion DVD. 

    This had never been done in book form, and after surviving the process we understood why! The legal issues alone were enough to almost make us abandon the effort. Microsoft did not want us to "distribute" a forensic image of a Windows system, so we had to zero out key Windows binaries to satisfy their lawyers. 

    The primary weakness of the book in 2017 is that operating systems have evolved, and many more forensics books have been written. It continues to be an interesting exercise to examine the forensic practices advocated by the book to see how they apply to more modern situations.

    This review of the book includes a summary of the contents:

    • Live incident response (collecting and analyzing volatile and nonvolatile data; 72 pp.)
    • Collecting and analyzing network-based data (live network surveillance and data analysis; 87 pp.)
    • Forensic duplication of various devices using commercial and open source tools (43 pp.)
    • Basic media analysis (deleted data recovery, metadata, hash analysis, “carving”/signature analysis, keyword searching, web browsing history, email, and registry analyses; 96 pp.)
    • Unknown tool/binary analysis (180 pp.)
    • Creating the “ultimate response CD” (response toolkit creation; 31 pp.)
    • Mobile device and removable media forensics (79 pp.)
    • On-line-based forensics (tracing emails and domain name ownership; 30 pp.)
    • Introduction to Perl scripting (12 pp.)

    After those three titles, I was done with writing for a while. However, in 2012 I taught a class for Black Hat in Abu Dhabi. I realized many of the students lacked the fundamental understanding of how networks operated and how network security monitoring could help them detect and respond to intrusions. I decided to write a book that would explain NSM from the ground up. While I assumed the reader would have familiarity with computing and some security concepts, I did not try to write the book for existing security experts.

    The result was The Practice of Network Security Monitoring: Understanding Incident Detection and Response. If you are new to NSM, this is the first book you should buy and read. It is a very popular title and it distills my philosophy and practice into the most digestible form, in 376 pages.

    The main drawback of the book is the integration of Security Onion coverage. SO is a wonderful open source suite, partly because it is kept so current. That makes it difficult for a print book to track changes in the software installation and configuration options. While you can still use PNSM to install and use SO, you are better off relying on Doug Burks' excellent online documentation. 

    PNSM is an awesome resource for learning how to use SO and other tools to detect and respond to intrusions. I am particularly pleased with chapter 9, on NSM operations. It is a joke that I often tell people to "read chapter 9" when anyone asks me about CIRTs.

    The introduction describes PNSM using these words:

    Part I, “Getting Started,” introduces NSM and how to think about sensor placement.

    • Chapter 1, “Network Security Monitoring Rationale,” explains why NSM matters, to help you gain the support needed to deploy NSM in your environment.
    • Chapter 2, “Collecting Network Traffic: Access, Storage, and Management,”addresses the challenges and solutions surrounding physical access to network traffic.

    Part II, “Security Onion Deployment,” focuses on installing SO on hardware and configuring SO effectively.

    • Chapter 3, “Stand-alone NSM Deployment and Installation,” introduces SO and explains how to install the software on spare hardware to gain initial NSM capability at low or no cost.
    • Chapter 4, “Distributed Deployment,” extends Chapter 3 to describe how to install a dispersed SO system.
    • Chapter 5, “SO Platform Housekeeping,” discusses maintenance activities for keeping your SO installation running smoothly. 

    Part III, “Tools,” describes key software shipped with SO and how to use these applications.

    • Chapter 6, “Command Line Packet Analysis Tools,” explains the key features of Tcpdump, Tshark, Dumpcap, and Argus in SO.
    • Chapter 7, “Graphical Packet Analysis Tools,” adds GUI-based software to the mix, describing Wireshark, Xplico, and NetworkMiner.
    • Chapter 8, “NSM Consoles,” shows how NSM suites, like Sguil, Squert, Snorby, and ELSA, enable detection and response workflows.

    Part IV, “NSM in Action,” discusses how to use NSM processes and data to detect and respond to intrusions.

    • Chapter 9, “NSM Operations,” shares my experience building and leading a global computer incident response team (CIRT).
    • Chapter 10, “Server-side Compromise,” is the first NSM case study, wherein you’ll learn how to apply NSM principles to identify and validate the compromise of an Internet-facing application.
    • Chapter 11, “Client-side Compromise,” is the second NSM case study, offering an example of a user being victimized by a client-side attack.
    • Chapter 12, “Extending SO,” concludes the main text with coverage of tools and techniques to expand SO’s capabilities.
    • Chapter 13, “Proxies and Checksums,” concludes the main text by addressing two challenges to conducting NSM.

    The Conclusion offers a few thoughts on the future of NSM, especially with respect to cloud environments. 

    The Appendix, “SO Scripts and Configuration,” includes information from SO developer Doug Burks on core SO configuration files and control scripts.

    I hope this post helps explain the different books I've written, as well as their applicability to modern security scenarios.


              Christian Chabot Net Worth: Age, Height, Weight, Bio        
    Christian Chabot Net Worth Christian Chabot made money by Celebrities niche. For all time, at the moment, 2017 year, Christian Chabot earned $27 Million. Exact sum is $27000000. Youtube Short biography, height, weight, dates: Pictures Summary Wikipedia Source: Christian Chabot
              Introducing Threat Operations: TO in Action        

    Posted under:

    As we wrap up our Introduction to Threat Operations series, let’s recap. We started by discussing why the way threats are handled hasn’t yielded the results the industry needs and how to think differently. Then we delved into what’s really required to keep pace with increasingly sophisticated adversaries: accelerating the human. To wrap up let’s use these concepts in a scenario to make them more tangible.

    We’ll tell the story of a high-tech component manufacturer named ComponentCo. Yes, we’ve been working overtime on creative naming. ComponentCo (CCo) makes products that go into the leading smartphone platform, making their intellectual property a huge target of interest to a variety of adversaries with different motives.

    • Competitors: Given CCo’s presence inside a platform that sells hundreds of millions of units a year, the competition is keenly trying to close the technology gap. A design win is worth hundreds of millions in revenue, so it’s not above these companies to gain parity any way they can.
    • Stock manipulators: Confidential information about new products and imminent design wins is gold to unscrupulous traders. But that’s not the only interesting information. If they can see manufacturing plans or unit projections, they will gain insight into device sales, opening up another avenue to profit from non-public information.
    • Nation-states: Many people claim nation-states hack to aid their own companies. That is likely true, but just as attractive is the opportunity to backdoor hundreds of millions of devices by manipulating their underlying components.

    ComponentCo already invests heavily in security. They monitor critical network segments. They capture packets in the DMZ and data center. They have a solid incident response process. Given the money at stake, they have pretty much every new, shiny object that promises to detect advanced attackers. But they are not naive. They are very clear about how vulnerable they are, mostly due to the sophistication of the various adversaries they face.

    As with many organizations, fielding a talented team to execute on their security program is challenging. There is a high-level CISO, as well as enough funding to maintain a team of dozens of security practitioners. But it’s not enough. So CCo is building a farm team. They recruit experienced professionals, but also high-potential system administrators from other parts of the business who they train in security. Bringing on less experienced folks has had mixed results – some of them have been able to figure it out, but others haven’t… as they expected when they started the farm team. They want to provide a more consistent training and job experience for these junior folks.

    Given that backdrop, what should ComponentCo do? They understand the need to think differently about attacks, and how important it is to move past a tactical view of threats to see the threat operation more broadly. They understand this way of looking at threats will help existing staff reach their potential, and more effectively protect information. This is what that looks like.

    Harness Threat Intel

    The first step in moving to a threat operations mindset is to make better use of threat intelligence, which starts with understanding adversaries. As described above, CCo contends with a variety of adversaries – including competitors, financially motivated hackers, and nation-states. That’s a wide array of threats, so CCo decided to purchase a number of threat feeds, each specializing in a different aspect of adversary activities.

    To leverage external threat data they aggregate it all into a platform built to reduce, normalize, and provide context. They looked at pumping the data directly into their SIEM, but at this time the flood of external data would have overwhelmed the existing SIEM. So they need yet another product to handle external threat data.

    They use their TI platform to alert based on knowledge of adversaries and likely attacks. But these alerts are not smoking guns – each is only the first step in a threat validation process which sends the alert back to the SIEM looking for supporting evidence of an actual attack. Given their confidence in this threat data, alerts from these sources have higher priority because they match known real-world attacks.

    Given what is at stake for CCo, they don’t want to miss anything. So they also integrate TI into some of their active controls – notably egress filters, IPS, and endpoint protection. This way they can quarantine devices communicating with known malicious sites or otherwise indicating a compromise before data is lost.

    Enrich Alerts

    We mentioned how an alert coming from the TI platform can be pushed to the SIEM for further investigation. But that’s only part of the story. The connection between SIEM and TI platform should be bidirectional, so when the SIEM fires an alert, information is pulled from the TI platform which corresponds to the adversary and attack.

    In case of an attack on CCo, an alert involving network reconnaissance, brute force password attacks, and finally privilege escalation would clearly indicate an active threat actor. So it would be helpful for the analyst performing initial validation to have access to all the IP addresses the potentially compromised device communicated with over the past week. These addresses may point to a specific bot network, and can provide a good clue to the most likely adversary. Of course it could be a false flag, but it still provides the analyst a head start when digging into the alert.

    Additional information useful to an analyst includes known indicators used by this adversary. This information helps to understand how an actor typically operates, and their likely next step. You can also save manual work by including network telemetry to/from the device for clues to whether the adversary has moved deeper into the network. Using destination network addresses you can also have a vulnerability scanner assess other targets to give the analyst what they need to quickly determine if any other devices have been compromised.

    Finally, given the indicators seen on the first detected device, internal security data could be mined to look for other instances of that attack regardless of whether network traffic shows the device acting strangely. Then the analyst can tell whether the attacker has been successful using the same tactic to establish other footholds in the environment. This is critical when it’s time to eradicate an adversary.

    This is pretty simple stuff which any semi-experienced analyst does as he/she validates an attack and assesses potential damage. The difference is all this data can be pulled automatically before an alert reaches the analyst. By the time an analyst starts to dig in, they shouldn’t have to start with a bunch of manual digging to get everything they need to investigate. They start validation in a good position to quickly understand what happened and assess the blast radius of the compromise.

    Building Trustable Automation

    Automation within threat operations can mean a lot of things. Assembling all the supporting information an analyst needs for threat validation prior to starting the process is clearly automation. But let’s move a little deeper into specific actions which can occur automatically. As described above, ComponentCo has a pretty mature response capability and typically removes all potentially compromised device from the network at the beginning of response to limit possible damage.

    But this impacts response in multiple ways. First, it may tip off the adversary, prompting them to burrow deeper and find other points of entry. Additionally, CCo loses their opportunity to monitor adversary activity to figure out what they were trying to do and how.

    Automation can help. CCo can automatically move a suspicious device onto a VLAN where all network traffic is captured, which won’t tip off the adversary to their discovery. They also start to pull EDR telemetry off the device at least every 30 minutes, to ensure data is captured even if the adversary is tampering with endpoint’s logs. This provides opportunity to see what adversaries are up to, and perhaps to establish preemptive workarounds in anticipation of the attacker’s next move.

    Another step CCo may add to their response playbook is to automatically update a network blacklist with any unknown external networks a compromised device has been communicating with, under the assumption they are likely botnets, and block traffic to them. They can search their network and device security data for other devices connecting to those networks, which can help identify additional compromised devices.

    Workflow and Process Automation

    Underlying all these functions is an automate first mentality, where the team builds playbooks which specify actions to take in response to typical threats. This is valuable for several reasons, including consistent response and minimization of human error. But scaling the security team is the most important. CCo is a very desirable place to work, and doesn’t generally have an issue finding talented folks, but skilled security staff are still in high demand. By combining a threat operations mindset with a heavy dose of automation, CCo can make less sophisticated (and cheaper) analysts more productive.

    Of course they still use Tier 3 analysts to handle tough and complicated incidents. But for others their playbooks can guide Tier 1 & 2 analysts. Let’s use an example of a response playbook for a phishing issue leads off a targeted attack.

    In our scenario a junior staffer in Finance received a phishing email claiming to come from his bank, and requiring immediate attention. The employee fell for the ruse and clicked the link, which compromised his device. The compromised device began internal reconnaissance and connected to a known botnet. At that point an alert triggered and the automated playbook kicked in, putting the device in a fully logged VLAN and increasing the monitoring level, then updating egress filters and the IPS configuration to watch for indicators corresponding to the initial attack. A full image of the device was taken prior to clean-up, and then it was restored and resumed normal operations quickly, without any real data loss or extensive manual effort.

    But given the sophistication of its adversaries, CCo doesn’t assume any phishing attack is just everyday phishing. So they install the image of the compromised device in a sandbox to see what it does. This secondary analysis shows the phishing attack was a diversion. A secondary malware kit activated the next day, which had all of the earmarks of far more sophisticated nation-state malware.

    So this gets immediately escalated to Tier 3.

    Handling a Targeted Threat

    Escalation of what appears to be a nation-state level attack triggers yet another playbook, which triggers the threat intel and alert enrichment functions discussed previously. By the time the case reaches a Tier 3 responder, they will quickly understand the adversary, their tactics, and where else similar attacks have been seen – inside or outside CCo.

    At this point the response team knows they are under real attack bt a sophisticated adversary, and automatically starts capturing egress traffic and locking down their most critical assets as a precaution. Because related information has already been collected and associated with this case, the Tier 3 analyst can very quickly figure out the adversary’s TTPs and choose an appropriate response.

    Obviously there is a lot more effort and detail to actually eradicate a nation-state from CCo’s systems, but they have a response process and playbook for that. The point to highlight here is that what looked like simple phishing, handled in a largely automated fashion, uncovered a sophisticated nation-state campaign. At that point the threat operations mindset enables CCo to seamlessly escalate and provides a Tier 3 analyst with all available information to streamline attack and adversary research, and accelerate both damage assessment and eventual eradication of the adversary.

    So what is required for this threat operations mindset?

    1. Define processes and playbooks: Consistent activity requires initial work to figure out appropriate responses for a number of different scenarios. The evolution always starts by defining how you want the team to behave, and then working to implement consistent processes.
    2. Implement an external threat data aggregation platform: External threat data is key to understanding what adversary you are facing and what they are likely to do. Numerous feeds are available, but to avoid overload and ensure can effectively utilize the data, you’ll want to aggregate and process it for better context.
    3. Integrate external and internal security data with analytics: Once aggregated, the external data needs to be analyzed alongside internal security data to pinpoint potential issues and identify patterns of malicious behavior based on what’s happening in the wild. At this point you get much more relevant alerts, enriched with supporting information about probable adversaries and indications of whether an attack has spread within your environment.
    4. Orchestrate existing monitors and controls: The key to operationalizing a playbook is to have all the systems work together. So your TI aggregation platform (if a separate technology) needs a bi-directional connection to and from your SIEM. It can also send data to IPS devices and egress filters to block known bad sites. It can check with an advanced endpoint tool to confirm that what is reported from the network actually happened on the endpoint, and vice-versa.
    5. Automate first: Finally, given all this analysis and integration, trusted automation can block traffic to known bad sites and move compromised devices into quarantine networks or capture telemetry on detection of suspicious activity. Basically, if something can be documented in a playbook, you should be able to automate much of the process.

    The end result is an orchestrated and automated ability to handle threats, equipping human analysts to do what they do best: pull on threads and make connections between isolated attacks which may represent sophisticated campaigns. Machines don’t do this well or automatically. If it can be enumerated in a playbook, it likely should be automated. If not it remains the purview of humans on the security team, and you can make them more productive by automatically aggregating the data they need to understand and address each situation.

    With that we wrap up our Threat Operations series. We’re always interested in feedback on our research, especially our scenarios. Just drop us an email, tweet, or comment on this post – we’re happy to discuss.

    - Mike Rothman (2) Comments Subscribe to our daily email digest
              Security for multirobot systems        
    Publish date: 
    March 20, 2017
    Article credit: 
    Larry Hardesty | MIT News Office
    research: 
    Yes
    MIT CSAIL latest news
    Press Contact: 

    Adam Conner-Simons, MIT CSAIL
    Email: aconner@csail.mit.edu
    Phone: (617) 324-9135
    MIT CSAIL

    Top Photo/Video
    Jason Dorfman, CSAIL photographer

    Distributed planning, communication, and control algorithms for autonomous robots make up a major area of research in computer science. But in the literature on multirobot systems, security has gotten relatively short shrift.

    Bottom Photo/Video
    Credit: 
    Jason Dorfman, CSAIL photographer
    stata_center_spotlight_image.jpg

    read more


              Security for multirobot systems        
    March 16, 2017
    Larry Hardesty | MIT News Office
    research: 
    Yes
    Top Image or Slideshow: 
    MIT CSAIL latest news
    Press Contact: 

    Adam Conner-Simons, MIT CSAIL
    Email: aconner@csail.mit.edu
    Phone: (617) 324-9135
    MIT CSAIL

    Distributed planning, communication, and control algorithms for autonomous robots make up a major area of research in computer science.

    read more


              Digital Underground Offering Cheap Botnets For Hire        

    Perhaps even the cyber-criminals are effected by the recent recession – botnets for hire are hitting rock-bottom rates starting at just $2. We reported back in April 2010 about the Texas Man Who Pleaded Guilty To Bot Network For Hire. They are becoming more multi-talented as well rather than just offering bot networks for DDoS […]

    The post Digital Underground Offering Cheap Botnets For Hire appeared first on Darknet - The Darkside.


              Texas Man Pleads Guilty To Bot Network For Hire        

    Another botnet herder bites the dust, the latest news in the malware arena is about David Anthony Edwards from Texas who has admitted he and his accomplice had offered tailor made malware and DDoS attacks for rent. 22,000 zombies is a reasonable number of bots for a herder to control on their own, and assuming […]

    The post Texas Man Pleads Guilty To Bot Network For Hire appeared first on Darknet - The Darkside.