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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InfoMasker: Preventing Eavesdropping Using Phoneme-Based Noise

Peng Huang (Zhejiang University), Yao Wei (Zhejiang University), Peng Cheng (Zhejiang University), Zhongjie Ba (Zhejiang University), Li Lu (Zhejiang University), Feng Lin (Zhejiang University), Fan Zhang (Zhejiang University), Kui Ren (Zhejiang University)

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Focusing on Pinocchio's Nose: A Gradients Scrutinizer to Thwart...

Jiayun Fu (Huazhong University of Science and Technology), Xiaojing Ma (Huazhong University of Science and Technology), Bin B. Zhu (Microsoft Research Asia), Pingyi Hu (Huazhong University of Science and Technology), Ruixin Zhao (Huazhong University of Science and Technology), Yaru Jia (Huazhong University of Science and Technology), Peng Xu (Huazhong University of Science and Technology), Hai…

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Towards Privacy-Preserving Platooning Services by means of Homomorphic Encryption

Nicolas Quero (Expleo France), Aymen Boudguiga (CEA LIST), Renaud Sirdey (CEA LIST), Nadir Karam (Expleo France)

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Commercial Vehicle Electronic Logging Device Security: Unmasking the Risk...

Jake Jepson, Rik Chatterjee, Jeremy Daily (Colorado State University)

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