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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Operationalizing Cybersecurity Research Ethics Review: From Principles and Guidelines...

Dennis Reidsma, Jeroen van der Ham, and Andrea Continella (University of Twente)

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Investigating the Impact of Evasion Attacks Against Automotive Intrusion...

Paolo Cerracchio, Stefano Longari, Michele Carminati, Stefano Zanero (Politecnico di Milano)

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Parakeet: Practical Key Transparency for End-to-End Encrypted Messaging

Harjasleen Malvai (UIUC/IC3), Lefteris Kokoris-Kogias (IST Austria), Alberto Sonnino (Mysten Labs), Esha Ghosh (Microsoft Research), Ercan Oztürk (Meta), Kevin Lewi (Meta), Sean Lawlor (Meta)

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