Jiang Zhang (University of Southern California), Konstantinos Psounis (University of Southern California), Muhammad Haroon (University of California, Davis), Zubair Shafiq (University of California, Davis)

Online behavioral advertising, and the associated tracking paraphernalia, poses a real privacy threat. Unfortunately, existing privacy-enhancing tools are not always effective against online advertising and tracking. We propose HARPO, a principled learning-based approach to subvert online behavioral advertising through obfuscation. HARPO uses reinforcement learning to adaptively interleave real page visits with fake pages to distort a tracker’s view of a user’s browsing profile. We evaluate HARPO against real-world user profiling and ad targeting models used for online behavioral advertising. The results show that HARPO improves privacy by triggering more than 40% incorrect interest segments and 6×higher bid values. HARPO outperforms existing obfuscation tools by as much as 16×for the same overhead. HARPO is also able to achieve better stealthiness to adversarial detection than existing obfuscation tools. HARPO meaningfully advances the state-of-the-art in leveraging obfuscation to subvert online behavioral advertising.

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Demo: A Simulator for Cooperative and Automated Driving Security

Mohammed Lamine Bouchouia (Telecom Paris - Institut Polytechnique de Paris), Jean-Philippe Monteuuis (Qualcomm), Houda Labiod (Telecom Paris - Institut Polytechnique de Paris), Ons Jelassi, Wafa Ben Jaballah (Thales) and Jonathan Petit (Telecom Paris - Institut Polytechnique de Paris)

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Speeding Dumbo: Pushing Asynchronous BFT Closer to Practice

Bingyong Guo (Institute of Software, Chinese Academy of Sciences), Yuan Lu (Institute of Software Chinese Academy of Sciences), Zhenliang Lu (The University of Sydney), Qiang Tang (The University of Sydney), jing xu (Institute of Software, Chinese Academy of Sciences), Zhenfeng Zhang (Institute of Software, Chinese Academy of Sciences)

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VPNInspector: Systematic Investigation of the VPN Ecosystem

Reethika Ramesh (University of Michigan), Leonid Evdokimov (Independent), Diwen Xue (University of Michigan), Roya Ensafi (University of Michigan)

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PoF: Proof-of-Following for Vehicle Platoons

Ziqi Xu (University of Arizona), Jingcheng Li (University of Arizona), Yanjun Pan (University of Arizona), Loukas Lazos (University of Arizona, Tucson), Ming Li (University of Arizona, Tucson), Nirnimesh Ghose (University of Nebraska–Lincoln)

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