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

Cyber Threat Intelligence for SOC Analysts

Nidhi Rastogi, Md Tanvirul Alam (Rochester Institute of Technology)

Read More

QUICforge: Client-side Request Forgery in QUIC

Yuri Gbur (Technische Universität Berlin), Florian Tschorsch (Technische Universität Berlin)

Read More

PISE: Protocol Inference using Symbolic Execution and Automata Learning

Ron Marcovich, Orna Grumberg, Gabi Nakibly (Technion, Israel Institute of Technology)

Read More