Hussein Darir (University of Illinois Urbana-Champaign), Geir Dullerud (University of Illinois Urbana-Champaign), Nikita Borisov (University of Illinois Urbana-Champaign)

We present ProbFlow, a probabilistic programming approach for estimating relay capacities in the Tor network. We refine previously derived probabilistic model of the network to take into account more of the complexity of the real-world Tor network. We use this model to perform inference in a probabilistic programming language called NumPyro which allows us to overcome the analytical barrier present in purely analytical approach. We integrate the implementation of ProbFlow to the current implementation of capacity estimation algorithms in the Tor network. We demonstrate the practical benefits of ProbFlow by simulating it in flow-based Python simulator and packet-based Shadow simulations, the highest fidelity simulator available for the Tor network. In both simulators, ProbFlow provides significantly more accurate estimates that results in improved user performance, with average download speeds increasing by 25% in the Shadow simulations.

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VulHawk: Cross-architecture Vulnerability Detection with Entropy-based Binary Code Search

Zhenhao Luo (College of Computer, National University of Defense Technology), Pengfei Wang (College of Computer, National University of Defense Technology), Baosheng Wang (College of Computer, National University of Defense Technology), Yong Tang (College of Computer, National University of Defense Technology), Wei Xie (College of Computer, National University of Defense Technology), Xu Zhou (College of Computer,…

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Folk Models of Misinformation on Social Media

Filipo Sharevski (DePaul University), Amy Devine (DePaul University), Emma Pieroni (DePaul University), Peter Jachim (DePaul University)

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Adventures in Wonderland: Automotive Cyber beyond the CAN Bus

Michael Westra (In-Vehicle Cyber Security Technical Manager, Ford)

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