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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Brokenwire: Wireless Disruption of CCS Electric Vehicle Charging

Sebastian Köhler (University of Oxford), Richard Baker (University of Oxford), Martin Strohmeier (armasuisse Science + Technology), Ivan Martinovic (University of Oxford)

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WIP: Towards the Practicality of the Adversarial Attack on...

Chen Ma (Xi'an Jiaotong University), Ningfei Wang (University of California, Irvine), Qi Alfred Chen (University of California, Irvine), Chao Shen (Xi'an Jiaotong University)

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Adventures in Wonderland: Automotive Cyber beyond the CAN Bus

Michael Westra (In-Vehicle Cyber Security Technical Manager, Ford)

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DOITRUST: Dissecting On-chain Compromised Internet Domains via Graph Learning

Shuo Wang (CSIRO's Data61 & Cybersecurity CRC, Australia), Mahathir Almashor (CSIRO's Data61 & Cybersecurity CRC, Australia), Alsharif Abuadbba (CSIRO's Data61 & Cybersecurity CRC, Australia), Ruoxi Sun (CSIRO's Data61), Minhui Xue (CSIRO's Data61), Calvin Wang (CSIRO's Data61), Raj Gaire (CSIRO's Data61 & Cybersecurity CRC, Australia), Surya Nepal (CSIRO's Data61 & Cybersecurity CRC, Australia), Seyit Camtepe (CSIRO's…

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