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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CLExtract: Recovering Highly Corrupted DVB/GSE Satellite Stream with Contrastive...

Minghao Lin (University of Colorado Boulder), Minghao Cheng (Independent Researcher), Dongsheng Luo (Florida International University), Yueqi Chen (University of Colorado Boulder) Presenter: Minghao Lin

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InfoMasker: Preventing Eavesdropping Using Phoneme-Based Noise

Peng Huang (Zhejiang University), Yao Wei (Zhejiang University), Peng Cheng (Zhejiang University), Zhongjie Ba (Zhejiang University), Li Lu (Zhejiang University), Feng Lin (Zhejiang University), Fan Zhang (Zhejiang University), Kui Ren (Zhejiang University)

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WIP: An Adaptive High Frequency Removal Attack to Bypass...

Yuki Hayakawa (Keio University), Takami Sato (University of California, Irvine), Ryo Suzuki, Kazuma Ikeda, Ozora Sako, Rokuto Nagata (Keio University), Qi Alfred Chen (University of California, Irvine), Kentaro Yoshioka (Keio University)

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VASP: V2X Application Spoofing Platform

Mohammad Raashid Ansari, Jonathan Petit, Jean-Philippe Monteuuis, Cong Chen (Qualcomm Technologies, Inc.)

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