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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Nick Ceccio, Naman Gupta, Majed Almansoori, Rahul Chatterjee (University of Wisconsin-Madison)

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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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BANS: Evaluation of Bystander Awareness Notification Systems for Productivity...

Shady Mansour (LMU Munich), Pascal Knierim (Universitat Innsbruck), Joseph O’Hagan (University of Glasgow), Florian Alt (University of the Bundeswehr Munich), Florian Mathis (University of Glasgow)

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Sometimes, You Aren’t What You Do: Mimicry Attacks against...

Akul Goyal (University of Illinois at Urbana-Champaign), Xueyuan Han (Wake Forest University), Gang Wang (University of Illinois at Urbana-Champaign), Adam Bates (University of Illinois at Urbana-Champaign)

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