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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Your Router is My Prober: Measuring IPv6 Networks via...

Long Pan (Tsinghua University), Jiahai Yang (Tsinghua University), Lin He (Tsinghua University), Zhiliang Wang (Tsinghua University), Leyao Nie (Tsinghua University), Guanglei Song (Tsinghua University), Yaozhong Liu (Tsinghua University)

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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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Adversarial Robustness for Tabular Data through Cost and Utility...

Klim Kireev (EPFL), Bogdan Kulynych (EPFL), Carmela Troncoso (EPFL)

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