$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

Protecting Internet users from becoming victimized attackers of click‐fraud

Journal of software : evolution and process, v.30 no.3, 2018년, pp.e1871 -   

Iqbal, Md Shahrear (School of Computing Queen's University Kingston Ontario Canada) ,  Zulkernine, Mohammad (School of Computing Queen's University Kingston Ontario Canada) ,  Jaafar, Fehmi (Ubitrak Saint‐) ,  Gu, Yuan (Laurent Quebec Canada)

Abstract AI-Helper 아이콘AI-Helper

AbstractInternet users are often victimized by malicious attackers. Some attackers infect and use innocent users' machines to launch large‐scale attacks without the users' knowledge. One of such attacks is the click‐fraud attack. Click‐fraud happens in pay‐per‐clic...

참고문헌 (48)

  1. Internet ad spend to reach $121b in 2014 23% of $537b total ad spend.http://techcrunch.com/2014/04/07/internet-ad-spend-to-reach-121b-in-2014-23-of-537b-total-ad-spend-ad-tech-gives-display-a-boost-over-search/. Accessed February 18 2015. 

  2. Mobile ad spending report.http://www.emarketer.com/Article/Mobile-Ad-Spend-Top-100-Billion-Worldwide-2016-51-of-Digital-Market/1012299. Accessed February 9 2016. 

  3. Wilbur, Kenneth C., Zhu, Yi. Click Fraud. Marketing science : the marketing journal of TIMS/ORSA, vol.28, no.2, 293-308.

  4. 10.1109/ICDCS.2008.98 ZhangL GuanY.Detecting click fraud in pay‐per‐click streams of online advertising networks.Proceedings of the 28th International Conference on Distributed Computing Systems (ICDCS) IEEE Beijing China;2008:77-84. 

  5. JuelsA StammS JakobssonM.Combating click fraud via premium clicks.USENIX Security vol. 70 Boston MA USA;2007. 

  6. 10.1145/2068816.2068843 Stone‐GrossB StevensR ZarrasA KemmererR KruegelC VignaG.Understanding fraudulent activities in online ad exchanges.Proceedings of the ACM SIGCOMM Conference on Internet Measurement ACM Berlin Germany;2011:279-294. 

  7. 10.1145/2377677.2377715 DaveV GuhaS ZhangY.Measuring and fingerprinting click‐spam in ad networks.Proceedings of the ACM SIGCOMM Conference on Applications Technologies Architectures and Protocols for Computer Communication ACM Helsinki Finland;2012:175-186. 

  8. 10.1145/2508859.2516688 DaveV GuhaS ZhangY.Viceroi: Catching click‐spam in search ad networks.Proceedings of the ACM SIGSAC Conference on Computer & Communications Security ACM Berlin Germany;2013:765-776. 

  9. Haddadi, Hamed. Fighting online click-fraud using bluff ads. Computer communication review, vol.40, no.2, 21-25.

  10. 10.1109/SECURWARE.2009.48 FeilyM ShahrestaniA RamadassS.A survey of botnet and botnet detection.Proceedings of the 3rd International Conference on Emerging Security Information Systems and Technologies (SECURWARE) IEEE Athens/Glyfada Greece;2009:268-273. 

  11. DaswaniN StoppelmanM.The anatomy of clickbot. a.Proceedings of the 1st Conference on Hot Topics in Understanding Botnets USENIX Association Cambridge MA USA;2007:1-11. 

  12. Digital ad industry will gain $8.2 billion by eliminating fraud and flaws in internet.http://www.iab.com/news/digital-ad-industry-will-gain-8-2-billion-by-eliminating-fraud-and-fraws-in-internet-supply-chain-iab-ey-study-shows/. Accessed February 6 2016. 

  13. 10.1109/HASE.2016.17 IqbalMS ZulkernineM JaafarF GuY.Fcfraud: fighting click‐fraud from the user side.Proceedings of the 16th IEEE International Symposium on High Assurance Systems Engineering (HASE 2016) IEEE;2016:157-164. 

  14. Facebook mobile ad revenue report.http://techcrunch.com/2016/01/27/facebook-earnings-q4-2015/. Accessed February 9 2016. 

  15. Kshetri, Nir. The Economics of Click Fraud. IEEE security & privacy, vol.8, no.3, 45-53.

  16. 10.1007/978-3-642-22424-9_10 MillerB PearceP GrierC KreibichC PaxsonV.What's clicking what? techniques and innovations of today's clickbots.Proceedings of the Detection of Intrusions and Malware and Vulnerability Assessment.Springer Amsterdam The Netherlands;2011:164-183. 

  17. Gandhi, Mona, Jakobsson, Markus, Ratkiewicz, Jacob. Badvertisements: Stealthy Click-Fraud with Unwitting Accessories. Journal of digital forensic practice, vol.1, no.2, 131-142.

  18. Jackson, Collin, Barth, Adam, Bortz, Andrew, Shao, Weidong, Boneh, Dan. Protecting browsers from DNS rebinding attacks. ACM transactions on the web, vol.3, no.1, 1-26.

  19. The spyware ‐ click‐fraud connection - and yahoo's role revisited.http://www.benedelman.org/news/040406-1.html#e1. Accessed July 9 2015. 

  20. Botnet implicated in click fraud scam.http://www.theregister.co.uk/2006/05/15/google_adword_scam/. Accessed July 9 2015. 

  21. Pandalabs uncovers a ‘pay per click’ botnet fraud.http://www.pandasecurity.com/about/press/viewnews.htm?noticia&=7368entorno&=ver&=pagina&=producto&=. Accessed July 9 2015. 

  22. Zeroaccess click‐fraud botnet.https://nakedsecurity.sophos.com/2015/01/31/zeroaccess-click-fraud-botnet-coughs-back-to-life/. Accessed April 9 2016. 

  23. Adwatcher: advanced click fraud detection.http://www.adwatcher.com/click-fraud-features.php. Accessed February 6 2015. 

  24. Clickcease: blocking click fraud.https://clickcease.com/. Accessed February 6 2015. 

  25. Clickreport: click fruad detection and monitoring.http://clickreport.com/click-fraud-prevention. Accessed February 6 2015. 

  26. MetwallyA AgrawalD AbbadiAE.Using association rules for fraud detection in web advertising networks.Proceedings of the 31st International Conference on Very Large Databases VLDB Endowment Trondheim Norway;2005:169-180. 

  27. 10.1145/1242572.1242606 MetwallyA AgrawalD El AbbadiA.Detectives: detecting coalition hit inflation attacks in advertising networks streams.Proceedings of the 16th International Conference on World Wide Web ACM Calgary Canada;2007:241-250. 

  28. Immorlica, N., Jain, K., Mahdian, M., Talwar, K.. Click Fraud Resistant Methods for Learning Click-Through Rates. Lecture notes in computer science, vol.3828, 34-45.

  29. Xu, H., Liu, D., Koehl, A., Wang, H., Stavrou, A.. Click Fraud Detection on the Advertiser Side. Lecture notes in computer science, vol.8713, 419-438.

  30. 10.1145/2414456.2414498 PearceP FeltAP NunezG WagnerD.Addroid: privilege separation for applications and advertisers in android.Proceedings of the 7th ACM Symposium on Information Computer and Communications Security ACM Seoul Republic of Korea;2012:71-72. 

  31. ShekharS DietzM WallachDS.Adsplit: separating smartphone advertising from applications.Proceedings of the 21st USENIX Security Symposium Bellevue WA USA;2012:553-567. 

  32. 10.1145/2594368.2594391 CrussellJ StevensR ChenH.Madfraud: investigating ad fraud in android applications.Proceedings of the 12th Annual International Conference on Mobile Systems Applications and Services ACM Bretton Woods NH USA;2014:123-134. 

  33. Cho, Geumhwan, Cho, Junsung, Song, Youngbae, Choi, Donghyun, Kim, Hyoungshick. Combating online fraud attacks in mobile-based advertising. Eurasip journal on information security, vol.2016, 2-.

  34. The libpcap project.http://sourceforge.net/projects/libpcap/. Accessed February 6 2015. 

  35. Easylist ad block filter.https://easylist.adblockplus.org/en/. Accessed February 6 2015. 

  36. Linux iptables pocket reference Purdy GN 2004 

  37. Hall, Mark, Frank, Eibe, Holmes, Geoffrey, Pfahringer, Bernhard, Reutemann, Peter, Witten, Ian H.. The WEKA data mining software : an update. SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowlege Discovery & Data Mining, vol.11, no.1, 10-18.

  38. Openbinder version 1.0.http://www.angryredplanet.com/~hackbod/openbinder/docs/html/index.html. Accessed February 5 2016. 

  39. C4. 5: programs for machine learning Quinlan JR 2014 

  40. J Mach Learn Breiman L 5 45 1 2001 10.1023/A:1010933404324 Random forests 

  41. Phantomjs: headless website browsing.http://phantomjs.org/. Accessed January 9 2015. 

  42. Selenium: browser automation.http://www.seleniumhq.org/. Accessed January 9 2015. 

  43. SisselJ.Xdotool‐fake keyboard/mouse input window management and more;2013. 

  44. Odroid xu3.http://www.hardkernel.com/main/products/prdt_info.php?g_code=G140448267127. Accessed July 9 2015. 

  45. Hardkernel.http://www.hardkernel.com/main/main.php. Accessed February 3 2016. 

  46. JacobsonV LeresC McCanneS.Tcpdump public repository. Web page athttp://www.tcpdump.org;2003. Accessed January 9 2015. 

  47. Odroid smart power.http://www.hardkernel.com/main/products/prdt_info.php?g_code=G137361754360. Accessed July 9 2015. 

  48. Bot fraud trend.the-bot-baseline-fraud-in-digital-advertisingthe-bot-baseline-fraud-in-digital-advertising. Accessed October 6 2016. 

관련 콘텐츠

저작권 관리 안내
섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로