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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Location Spoofing Attacks on Autonomous Fleets

Jinghan Yang, Andew Estornell, Yevgeniy Vorobeychik (Washington University in St. Louis)

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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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Short: Rethinking Secure Pairing in Drone Swarms

Muslum Ozgur Ozmen, Habiba Farrukh, Hyungsub Kim, Antonio Bianchi, Z. Berkay Celik (Purdue University)

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The Advantages of Distributed TCAM Firewalls in Automotive Real-Time...

Evan Allen (Virginia Tech), Zeb Bowden (Virginia Tech Transportation Institute), J. Scot Ransbottom (Virginia Tech)

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