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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FUZZILLI: Fuzzing for JavaScript JIT Compiler Vulnerabilities

Samuel Groß (Google), Simon Koch (TU Braunschweig), Lukas Bernhard (Ruhr-University Bochum), Thorsten Holz (CISPA Helmholtz Center for Information Security), Martin Johns (TU Braunschweig)

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Securing EV charging system against Physical-layer Signal Injection Attack...

Soyeon Son (Korea University) Kyungho Joo (Korea University) Wonsuk Choi (Korea University) Dong Hoon Lee (Korea University)

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Cyber Threat Intelligence for SOC Analysts

Nidhi Rastogi, Md Tanvirul Alam (Rochester Institute of Technology)

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