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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ReScan: A Middleware Framework for Realistic and Robust Black-box...

Kostas Drakonakis (FORTH), Sotiris Ioannidis (Technical University of Crete), Jason Polakis (University of Illinois at Chicago)

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OBSan: An Out-Of-Bound Sanitizer to Harden DNN Executables

Yanzuo Chen (The Hong Kong University of Science and Technology), Yuanyuan Yuan (The Hong Kong University of Science and Technology), Shuai Wang (The Hong Kong University of Science and Technology)

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Empirical Scanning Analysis of Censys and Shodan

Christopher Bennett, AbdelRahman Abdou, and Paul C. van Oorschot (School of Computer Science, Carleton University, Canada)

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Efficient Privacy-Preserved Processing of Multimodal Data for Vehicular Traffic...

Meisam Mohammady (Iowa State University), Reza Arablouei (Data61, CSIRO)

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Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)