Web privacy measurement has often focused on the implementation specifics of various tracking techniques, developing ways to block them, and producing browser add-ons which demonstrate such blocking. However, while over 20 years of this focus has yielded lots of papers, citations, and media coverage, there has been limited real-world impact. A much more promising approach to effecting systemic change at scale is to shift attention away from how tracking is performed towards evaluating if such tracking is compliant with a growing body of applicable regulations.

In this talk I will offer perspectives on compliance measurement at scale, drawing lessons from my experience in the worlds of academic research, civil liberties advocacy, class litigation, and industry. Common themes will be explored and large-scale compliance measurement technologies will be presented in-depth. Likewise, insights on how computer scientists may effectively work across and between disciplinary boundaries will be presented. Ultimately, the most effective means to achieve change at scale is not to build another add-on, it is to build coalitions of experts working together to ensure technology, business, and regulation exist in harmony.

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REaaS: Enabling Adversarially Robust Downstream Classifiers via Robust Encoder...

Wenjie Qu (Huazhong University of Science and Technology), Jinyuan Jia (University of Illinois Urbana-Champaign), Neil Zhenqiang Gong (Duke University)

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He-HTLC: Revisiting Incentives in HTLC

Sarisht Wadhwa (Duke University), Jannis Stoeter (Duke University), Fan Zhang (Duke University, Yale University), Kartik Nayak (Duke University)

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CROW: Code Diversification for WebAssembly

Javier Cabrera Arteaga, Orestis Floros, Benoit Baudry, Martin Monperrus (KTH Royal Institute of Technology), Oscar Vera Perez (Univ Rennes, Inria, CNRS, IRISA)

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