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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DARWIN: Survival of the Fittest Fuzzing Mutators

Patrick Jauernig (Technical University of Darmstadt), Domagoj Jakobovic (University of Zagreb, Croatia), Stjepan Picek (Radboud University and TU Delft), Emmanuel Stapf (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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Learning Automated Defense Strategies Using Graph-Based Cyber Attack Simulations

Jakob Nyber, Pontus Johnson (KTH Royal Institute of Technology)

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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)

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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)

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