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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Semi-Automated Synthesis of Driving Rules

Diego Ortiz, Leilani Gilpin, Alvaro A. Cardenas (University of California, Santa Cruz)

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A Case Study on Fuzzing Satellite Firmware

Tobias Scharnowski and Felix Buchmann (Ruhr-Universitat Bochum), Simon Woerner and Thorsten Holz (CISPA Helmholtz Center for Information Security) Presenter: Tobias Scharnowski

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Thwarting Smartphone SMS Attacks at the Radio Interface Layer

Haohuang Wen (Ohio State University), Phillip Porras (SRI International), Vinod Yegneswaran (SRI International), Zhiqiang Lin (Ohio State University)

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