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

Fine-Grained Trackability in Protocol Executions

Ksenia Budykho (Surrey Centre for Cyber Security, University of Surrey, UK), Ioana Boureanu (Surrey Centre for Cyber Security, University of Surrey, UK), Steve Wesemeyer (Surrey Centre for Cyber Security, University of Surrey, UK), Daniel Romero (NCC Group), Matt Lewis (NCC Group), Yogaratnam Rahulan (5G/6G Innovation Centre - 5GIC/6GIC, University of Surrey, UK), Fortunat Rajaona (Surrey…

Read More

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

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

Read More

FUZZILLI: Fuzzing for JavaScript JIT Compiler Vulnerabilities

Samuel Groß (Google), Simon Koch (TU Braunschweig), Lukas Bernhard (Ruhr-University Bochum), Thorsten Holz (CISPA Helmholtz Center for Information Security), Martin Johns (TU Braunschweig)

Read More

Cyber Threat Intelligence for SOC Analysts

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

Read More