Diwen Xue (University of Michigan), Robert Stanley (University of Michigan), Piyush Kumar (University of Michigan), Roya Ensafi (University of Michigan)

The escalating global trend of Internet censorship has necessitated an increased adoption of proxy tools, especially obfuscated circumvention proxies. These proxies serve a fundamental need for access and connectivity among millions in heavily censored regions. However, as the use of proxies expands, so do censors' dedicated efforts to detect and disrupt such circumvention traffic to enforce their information control policies.

In this paper, we bring out the presence of an inherent fingerprint for detecting obfuscated proxy traffic. The fingerprint is created by the misalignment of transport- and application-layer sessions in proxy routing, which is reflected in the discrepancy in Round Trip Times (RTTs) across network layers. Importantly, being protocol-agnostic, the fingerprint enables an adversary to effectively target multiple proxy protocols simultaneously. We conduct an extensive evaluation using both controlled testbeds and real-world traffic, collected from a partner ISP, to assess the fingerprint's potential for exploitation by censors. In addition to being of interest on its own, our timing-based fingerprinting vulnerability highlights the deficiencies in existing obfuscation approaches. We hope our study brings the attention of the circumvention community to packet timing as an area of concern and leads to the development of more sustainable countermeasures.

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Ring of Gyges: Accountable Anonymous Broadcast via Secret-Shared Shuffle

Wentao Dong (City University of Hong Kong), Peipei Jiang (Wuhan University; City University of Hong Kong), Huayi Duan (ETH Zurich), Cong Wang (City University of Hong Kong), Lingchen Zhao (Wuhan University), Qian Wang (Wuhan University)

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Moneta: Ex-Vivo GPU Driver Fuzzing by Recalling In-Vivo Execution...

Joonkyo Jung (Department of Computer Science, Yonsei University), Jisoo Jang (Department of Computer Science, Yonsei University), Yongwan Jo (Department of Computer Science, Yonsei University), Jonas Vinck (DistriNet, KU Leuven), Alexios Voulimeneas (CYS, TU Delft), Stijn Volckaert (DistriNet, KU Leuven), Dokyung Song (Department of Computer Science, Yonsei University)

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Reinforcement Unlearning

Dayong Ye (University of Technology Sydney), Tianqing Zhu (City University of Macau), Congcong Zhu (City University of Macau), Derui Wang (CSIRO’s Data61), Kun Gao (University of Technology Sydney), Zewei Shi (CSIRO’s Data61), Sheng Shen (Torrens University Australia), Wanlei Zhou (City University of Macau), Minhui Xue (CSIRO's Data61)

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