WebGraph: Capturing Advertising and Tracking Information Flows for Robust Blocking
Sandra Siby,
Umar Iqbal,
Steven Englehardt
et al.
Abstract:Millions of web users directly depend on ad and tracker blocking tools to protect their privacy. However, existing ad and tracker blockers fall short because of their reliance on trivially susceptible advertising and tracking content. In this paper, we first demonstrate that the state-of-the-art machine learning based ad and tracker blockers, such as ADGRAPH, are susceptible to adversarial evasions deployed in real-world. Second, we introduce WEBGRAPH, the first graph-based machine learning blocker that detect… Show more
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