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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The “Beatrix” Resurrections: Robust Backdoor Detection via Gram Matrices

Wanlun Ma (Swinburne University of Technology), Derui Wang (CSIRO’s Data61), Ruoxi Sun (The University of Adelaide & CSIRO's Data61), Minhui Xue (CSIRO's Data61), Sheng Wen (Swinburne University of Technology), Yang Xiang (Digital Research & Innovation Capability Platform, Swinburne University of Technology)

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Measuring Messengers: Analyzing Infrastructures and Message Timings to Extract...

Theodor Schnitzler (Research Center Trustworthy Data Science and Security, TU Dortmund, and Ruhr-Universität Bochum)

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Breaking and Fixing Virtual Channels: Domino Attack and Donner

Lukas Aumayr (TU Wien), Pedro Moreno-Sanchez (IMDEA Software Institute), Aniket Kate (Purdue University / Supra), Matteo Maffei (Christian Doppler Laboratory Blockchain Technologies for the Internet of Things / TU Wien)

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FCGAT: Interpretable Malware Classification Method using Function Call Graph...

Minami Someya (Institute of Information Security), Yuhei Otsubo (National Police Academy), Akira Otsuka (Institute of Information Security)

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