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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RAI2: Responsible Identity Audit Governing the Artificial Intelligence

Tian Dong (Shanghai Jiao Tong University), Shaofeng Li (Shanghai Jiao Tong University), Guoxing Chen (Shanghai Jiao Tong University), Minhui Xue (CSIRO's Data61), Haojin Zhu (Shanghai Jiao Tong University), Zhen Liu (Shanghai Jiao Tong University)

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Why do Internet Devices Remain Vulnerable? A Survey with...

Tamara Bondar, Hala Assal, AbdelRahman Abdou (Carleton University)

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BlockScope: Detecting and Investigating Propagated Vulnerabilities in Forked Blockchain...

Xiao Yi (The Chinese University of Hong Kong), Yuzhou Fang (The Chinese University of Hong Kong), Daoyuan Wu (The Chinese University of Hong Kong), Lingxiao Jiang (Singapore Management University)

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A Transcontinental Analysis of Account Remediation Protocols of Popular...

Philipp Markert (Ruhr University Bochum), Andrick Adhikari (University of Denver), Sanchari Das (University of Denver)

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