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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WIP: Body Posture Analysis as an Objective Measurement for...

Cherin Lim, Tianhao Xu, Prashanth Rajivan (University of Washington)

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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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Non-Interactive Privacy-Preserving Sybil-Free Authentication Scheme in VANETs

Mahdi Akil (Karlstad University), Leonardo Martucci (Karlstad University), Jaap-Henk Hoepman (Radboud University)

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Tag of the Dead: How Terminated SaaS Tags Become...

Takahito Sakamoto, Takuya Murozono (DataSign Inc)

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