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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WIP: A First Look At Employing Large Multimodal Models...

Mohammed Aldeen, Pedram MohajerAnsari, Jin Ma, Mashrur Chowdhury, Long Cheng, Mert D. Pesé (Clemson University)

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POSE: Practical Off-chain Smart Contract Execution

Tommaso Frassetto (Technical University of Darmstadt), Patrick Jauernig (Technical University of Darmstadt), David Koisser (Technical University of Darmstadt), David Kretzler (Technical University of Darmstadt), Benjamin Schlosser (Technical University of Darmstadt), Sebastian Faust (Technical University of Darmstadt), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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podft: On Accelerating Dynamic Taint Analysis with Precise Path...

Zhiyou Tian (Xidian University), Cong Sun (Xidian University), Dongrui Zeng (Palo Alto Networks), Gang Tan (Pennsylvania State University)

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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)

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