Ashish Hooda (University of Wisconsin-Madison), Andrey Labunets (UC San Diego), Tadayoshi Kohno (University of Washington), Earlence Fernandes (UC San Diego)

Content scanning systems employ perceptual hashing algorithms to scan user content for illegal material, such as child pornography or terrorist recruitment flyers. Perceptual hashing algorithms help determine whether two images are visually similar while preserving the privacy of the input images. Several efforts from industry and academia propose scanning on client devices such as smartphones due to the impending rollout of end-to-end encryption that will make server-side scanning difficult. These proposals have met with strong criticism because of the potential for the technology to be misused for censorship. However, the risks of this technology in the context of surveillance are not well understood. Our work informs this conversation by experimentally characterizing the potential for one type of misuse --- attackers manipulating the content scanning system to perform physical surveillance on target locations. Our contributions are threefold: (1) we offer a definition of physical surveillance in the context of client-side image scanning systems; (2) we experimentally characterize this risk and create a surveillance algorithm that achieves physical surveillance rates of more than 30% by poisoning 0.2% of the perceptual hash database; (3) we experimentally study the trade-off between the robustness of client-side image scanning systems and surveillance, showing that more robust detection of illegal material leads to an increased potential for physical surveillance in most settings.

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Automatic Policy Synthesis and Enforcement for Protecting Untrusted Deserialization

Quan Zhang (Tsinghua University), Yiwen Xu (Tsinghua University), Zijing Yin (Tsinghua University), Chijin Zhou (Tsinghua University), Yu Jiang (Tsinghua University)

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WIP: Shadow Hack: Adversarial Shadow Attack Against LiDAR Object...

Ryunosuke Kobayashi, Kazuki Nomoto, Yuna Tanaka, Go Tsuruoka (Waseda University), Tatsuya Mori (Waseda University/NICT/RIKEN)

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CAGE: Complementing Arm CCA with GPU Extensions

Chenxu Wang (Southern University of Science and Technology (SUSTech) and The Hong Kong Polytechnic University), Fengwei Zhang (Southern University of Science and Technology (SUSTech)), Yunjie Deng (Southern University of Science and Technology (SUSTech)), Kevin Leach (Vanderbilt University), Jiannong Cao (The Hong Kong Polytechnic University), Zhenyu Ning (Hunan University), Shoumeng Yan (Ant Group), Zhengyu He (Ant…

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