Abstract
Targeted advertisement is prevalent on the Web. Many privacyenhancing tools have been developed to thwart targeted advertisement. Adblock Plus is one such popular tool, used by millions of users on a daily basis, to block unwanted ads and trackers. Adblock Plus uses EasyList and EasyPrivacy, the most prominent and widely used open-source filters, to block unwanted web contents. However, Adblock Plus, by default, also enables an exception list to unblock web requests that comply with specific guidelines defined by the Acceptable Ads Committee. Any publisher can enroll into the Acceptable Ads initiative to request the unblocking of web contents. Adblock Plus in return charges a licensing fee from large entities, who gain a significant amount of ad impressions per month due to participation in the Acceptable Ads initiative. However, the privacy implications of the default inclusion of the exception list has not been well studied, especially as it can unblock not only ads, but also trackers (e.g., unblocking contents otherwise blocked by EasyPrivacy). In this paper, we take a data-driven approach, where we collect historical updates made to Adblock Plus’s exception list and real-world web traffic by visiting the top 10k websites listed by Tranco. Using such data we analyze not only how the exception list has evolved over the years in terms of both contents unblocked and partners/entities enrolled into the Acceptable Ads initiative, but also the privacy implications of enabling the exception list by default. We found that Google not only unblocks the most number of unique domains, but is also unblocked by the most number of unique partners. From our traffic analysis, we see that of the 42,210 Google bound web requests, originally blocked by EasyPrivacy, around 80% of such requests are unblocked by the exception list. More worryingly, many of the requests enable 1-by-1 tracking pixel images. We, therefore, question exception rules that negate EasyPrivacy filtering rules by default and advocate for a better vetting process.
Dilawer Ahmed
Phd Student
My research interests include distributed robotics, mobile computing and programmable matter.