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.

View More Papers

ProbFlow : Using Probabilistic Programming in Anonymous Communication Networks

Hussein Darir (University of Illinois Urbana-Champaign), Geir Dullerud (University of Illinois Urbana-Champaign), Nikita Borisov (University of Illinois Urbana-Champaign)

Read More

A Transcontinental Analysis of Account Remediation Protocols of Popular...

Philipp Markert (Ruhr University Bochum), Andrick Adhikari (University of Denver), Sanchari Das (University of Denver)

Read More

StealthyIMU: Stealing Permission-protected Private Information From Smartphone Voice Assistant...

Ke Sun (University of California San Diego), Chunyu Xia (University of California San Diego), Songlin Xu (University of California San Diego), Xinyu Zhang (University of California San Diego)

Read More