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

We estimate vehicular traffic states from multi-modal data collected by single-loop detectors while preserving the privacy of the individual vehicles contributing to the data. To this end, we propose a novel hybrid differential privacy (DP) approach that utilizes minimal randomization to preserve privacy by taking advantage of the relevant traffic state dynamics and the concept of DP sensitivity. Through theoretical analysis and experiments with real-world data, we show that the proposed approach significantly outperforms the related baseline non-private and private approaches in terms of accuracy and privacy preservation.

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Securing Lidar Communication through Watermark-based Tampering Detection (Long)

Michele Marazzi, Stefano Longari, Michele Carminati, Stefano Zanero (Politecnico di Milano)

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Tactics, Threats & Targets: Modeling Disinformation and its Mitigation

Shujaat Mirza (New York University), Labeeba Begum (New York University Abu Dhabi), Liang Niu (New York University), Sarah Pardo (New York University Abu Dhabi), Azza Abouzied (New York University Abu Dhabi), Paolo Papotti (EURECOM), Christina Pöpper (New York University Abu Dhabi)

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Ghost Domain Reloaded: Vulnerable Links in Domain Name Delegation...

Xiang Li (Tsinghua University), Baojun Liu (Tsinghua University), Xuesong Bai (University of California, Irvine), Mingming Zhang (Tsinghua University), Qifan Zhang (University of California, Irvine), Zhou Li (University of California, Irvine), Haixin Duan (Tsinghua University; QI-ANXIN Technology Research Institute; Zhongguancun Laboratory), Qi Li (Tsinghua University; Zhongguancun Laboratory)

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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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