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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Cybersecurity of COSPAS-SARSAT and EPIRB: threat and attacker models,...

Andrei Costin, Hannu Turtiainen, Syed Khandkher and Timo Hamalainen (Faculty of Information Technology, University of Jyvaskyla, Finland) Presenter: Andrei Costin

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User Attitudes Towards Controls for Ad Interests Estimated On-device...

Florian Lachner, Minzhe Yuan Chen Cheng, Theodore Olsauskas-Warren (Google)

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Understanding the Ethical Frameworks of Internet Measurement Studies

Eric Pauley and Patrick McDaniel (University of Wisconsin–Madison)

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Reminding Drivers of the Stalking Vehicles on the Road

Wei Sun, Kannan Srinivsan (The Ohio State University)

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