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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Exploiting Diagnostic Protocol Vulnerabilities on Embedded Networks in Commercial...

Carson Green, Rik Chatterjee, Jeremy Daily (Colorado State University)

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On the Anonymity of Peer-To-Peer Network Anonymity Schemes Used...

Piyush Kumar Sharma (imec-COSIC, KU Leuven), Devashish Gosain (Max Planck Institute for Informatics), Claudia Diaz (Nym Technologies, SA and imec-COSIC, KU Leuven)

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Navigating Murky Waters: Automated Browser Feature Testing for Uncovering...

Mir Masood Ali (University of Illinois Chicago), Binoy Chitale (Stony Brook University), Mohammad Ghasemisharif (University of Illinois Chicago), Chris Kanich (University of Illinois Chicago), Nick Nikiforakis (Stony Brook University), Jason Polakis (University of Illinois Chicago)

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Ethical Challenges in Blockchain Network Measurement Research

Yuzhe Tang (Syracuse University), Kai Li (San Diego State University), and Yibo Wang and Jiaqi Chen (Syracuse University)

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