AutoFR: Automated Filter Rule Generation for Adblocking

Adblocking relies on filter lists, which are manually curated and maintained by a small community of filter list authors. This manual process is laborious and does not scale well to a large number of sites and over time. We introduce AutoFR, a …

OVRSeen: Auditing Network Traffic and Privacy Policies in Oculus VR

Virtual reality (VR) is an emerging technology that enables new applications but also introduces privacy risks. In this paper, we focus on Oculus VR (OVR), the leading platform in the VR space, and we provide the first comprehensive analysis of …

CV-Inspector: Towards Automating Detection of Adblock Circumvention

The adblocking arms race has escalated over the last few years. An entire new ecosystem of circumvention (CV) services has recently emerged that aims to bypass adblockers by obfuscating site content, making it difficult for adblocking filter lists to distinguish between ads and functional content. In this paper, we investigate recent anti-circumvention efforts by the adblocking community that leverage custom filter lists. In particular, we analyze the anti-circumvention filter list (ACVL), which supports advanced filter rules with enriched syntax and capabilities designed specifically to counter circumvention. To help automate and scale ACVL curation, we develop CV-INSPECTOR, a machine learning approach for automatically detecting adblock circumvention using differential execution analysis.

The TV is Smart and Full of Trackers: Measuring Smart TV Advertising and Tracking

In this paper, we present a large-scale measurement study of the smart TV advertising and tracking ecosystem.