Mahdi Rahimi (KU Leuven), Piyush Kumar Sharma (KU Leuven), Claudia Diaz (KU Leuven)

Anonymous communication systems such as mix networks achieve anonymity at the expense of latency that is introduced to alter the flow of packets and hinder their tracing. A high latency however has a negative impact on usability. In this work, we propose LARMix, a novel latency-aware routing scheme for mixnets that reduces propagation latency with a limited impact on anonymity. LARMix can achieve this while also load balancing the traffic in the network. We additionally show how a network can be configured to maximize anonymity while meeting an average end-to-end latency constraint. Lastly, we perform a security analysis studying various adversarial strategies and conclude that LARMix does not significantly increase adversarial advantage as long as the adversary is not able to selectively compromise mixnodes after the LARMix routing policy has been computed.

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SigmaDiff: Semantics-Aware Deep Graph Matching for Pseudocode Diffing

Lian Gao (University of California Riverside), Yu Qu (University of California Riverside), Sheng Yu (University of California, Riverside & Deepbits Technology Inc.), Yue Duan (Singapore Management University), Heng Yin (University of California, Riverside & Deepbits Technology Inc.)

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Commercial Vehicle Electronic Logging Device Security: Unmasking the Risk...

Jake Jepson, Rik Chatterjee, Jeremy Daily (Colorado State University)

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Aligning Confidential Computing with Cloud-native ML Platforms

Angelo Ruocco, Chris Porter, Claudio Carvalho, Daniele Buono, Derren Dunn, Hubertus Franke, James Bottomley, Marcio Silva, Mengmei Ye, Niteesh Dubey, Tobin Feldman-Fitzthum (IBM Research)

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