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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Do Not Give a Dog Bread Every Time He...

Chongqing Lei (Southeast University), Zhen Ling (Southeast University), Yue Zhang (Jinan University), Kai Dong (Southeast University), Kaizheng Liu (Southeast University), Junzhou Luo (Southeast University), Xinwen Fu (University of Massachusetts Lowell)

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Drone Security and the Mysterious Case of DJI's DroneID

Nico Schiller (Ruhr-Universität Bochum), Merlin Chlosta (CISPA Helmholtz Center for Information Security), Moritz Schloegel (Ruhr-Universität Bochum), Nils Bars (Ruhr University Bochum), Thorsten Eisenhofer (Ruhr University Bochum), Tobias Scharnowski (Ruhr-University Bochum), Felix Domke (Independent), Lea Schönherr (CISPA Helmholtz Center for Information Security), Thorsten Holz (CISPA Helmholtz Center for Information Security)

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WIP: Adversarial Retroreflective Patches: A Novel Stealthy Attack on...

Go Tsuruoka (Waseda University), Takami Sato, Qi Alfred Chen (University of California, Irvine), Kazuki Nomoto, Ryunosuke Kobayashi, Yuna Tanaka (Waseda University), Tatsuya Mori (Waseda University/NICT/RIKEN)

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