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

Cybersecurity of COSPAS-SARSAT and EPIRB: threat and attacker models,...

Andrei Costin, Hannu Turtiainen, Syed Khandkher and Timo Hamalainen (Faculty of Information Technology, University of Jyvaskyla, Finland) Presenter: Andrei Costin

Read More

Short: Certifiably Robust Perception Against Adversarial Patch Attacks: A...

Chong Xiang (Princeton University), Chawin Sitawarin (University of California, Berkeley), Tong Wu (Princeton University), Prateek Mittal (Princeton University)

Read More

RoVISQ: Reduction of Video Service Quality via Adversarial Attacks...

Jung-Woo Chang (University of California San Diego), Mojan Javaheripi (University of California San Diego), Seira Hidano (KDDI Research, Inc.), Farinaz Koushanfar (University of California San Diego)

Read More

BANS: Evaluation of Bystander Awareness Notification Systems for Productivity...

Shady Mansour (LMU Munich), Pascal Knierim (Universitat Innsbruck), Joseph O’Hagan (University of Glasgow), Florian Alt (University of the Bundeswehr Munich), Florian Mathis (University of Glasgow)

Read More