TY - GEN
T1 - Your online interests-Pwned! A pollution attack against targeted advertising
AU - Meng, Wei
AU - Xing, Xinyu
AU - Sheth, Anmol
AU - Weinsberg, Udi
AU - Lee, Wenke
PY - 2014/11/3
Y1 - 2014/11/3
N2 - We present a new ad fraud mechanism that enables publishers to increase their ad revenue by deceiving the ad exchange and advertisers to target higher paying ads at users visiting the publisher's site. Our attack is based on polluting users' online interest profile by issuing requests to content not explicitly requested by the user, such that it influences the ad selection process. We address several challenges involved in setting up the attack for the two most commonly used ad targeting mechanisms-re-marketing and behavioral targeting. We validate the attack for one of the largest ad exchanges and empirically measure the monetary gains of the publisher by emulating the attack using web traces of 619 real users. Our results show that the attack is effective in biasing ads towards the desired higher-paying advertisers; the polluter can influence up to 74% and 12% of the total ad impressions for re-marketing and behavioral pollution, respectively. The attack is robust to diverse browsing patterns and online interests of users. Finally, the attack is lucrative and on average the attack can increase revenue of fraudulent publishers by as much as 33%.
AB - We present a new ad fraud mechanism that enables publishers to increase their ad revenue by deceiving the ad exchange and advertisers to target higher paying ads at users visiting the publisher's site. Our attack is based on polluting users' online interest profile by issuing requests to content not explicitly requested by the user, such that it influences the ad selection process. We address several challenges involved in setting up the attack for the two most commonly used ad targeting mechanisms-re-marketing and behavioral targeting. We validate the attack for one of the largest ad exchanges and empirically measure the monetary gains of the publisher by emulating the attack using web traces of 619 real users. Our results show that the attack is effective in biasing ads towards the desired higher-paying advertisers; the polluter can influence up to 74% and 12% of the total ad impressions for re-marketing and behavioral pollution, respectively. The attack is robust to diverse browsing patterns and online interests of users. Finally, the attack is lucrative and on average the attack can increase revenue of fraudulent publishers by as much as 33%.
UR - http://www.scopus.com/inward/record.url?scp=84910676882&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84910676882&partnerID=8YFLogxK
U2 - 10.1145/2660267.2687258
DO - 10.1145/2660267.2687258
M3 - Conference contribution
AN - SCOPUS:84910676882
SN - 9781450329576
T3 - Proceedings of the ACM Conference on Computer and Communications Security
SP - 129
EP - 140
BT - Proceedings of the ACM Conference on Computer and Communications Security
PB - Association for Computing Machinery
T2 - 21st ACM Conference on Computer and Communications Security, CCS 2014
Y2 - 3 November 2014 through 7 November 2014
ER -