Hsun Lee (National Taiwan University), Yuming Hsu (National Taiwan University), Jing-Jie Wang (National Taiwan University), Hao Cheng Yang (National Taiwan University), Yu-Heng Chen (National Taiwan University), Yih-Chun Hu (University of Illinois at Urbana-Champaign), Hsu-Chun Hsiao (National Taiwan University)

Generating randomness by public participation allows participants to contribute randomness directly and verify the result's security. Ideally, the difficulty of participating in such activities should be as low as possible to reduce the computational burden of being a contributor. However, existing randomness generation protocols are unsuitable for this scenario because of scalability or usability issues. Hence, in this paper we present HeadStart, a participatory randomness protocol designed for public participation at scale. HeadStart allows contributors to verify the result on commodity devices efficiently, and provides a parameter $L$ that can make the result-publication latency $L$ times lower. Additionally, we propose two implementation improvements to speed up the verification further and reduce the proof size. The verification complexity of HeadStart is only $O(L times polylog(T) +log C)$ for a contribution phase lasting for time $T$ with $C$ contributions.

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Fine-Grained Coverage-Based Fuzzing

Bernard Nongpoh (Université Paris Saclay), Marwan Nour (Université Paris Saclay), Michaël Marcozzi (Université Paris Saclay), Sébastien Bardin (Université Paris Saclay)

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FirmWire: Transparent Dynamic Analysis for Cellular Baseband Firmware

Grant Hernandez (University of Florida), Marius Muench (Vrije Universiteit Amsterdam), Dominik Maier (TU Berlin), Alyssa Milburn (Vrije Universiteit Amsterdam), Shinjo Park (TU Berlin), Tobias Scharnowski (Ruhr-University Bochum), Tyler Tucker (University of Florida), Patrick Traynor (University of Florida), Kevin Butler (University of Florida)

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Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Pablo Moriano (Oak Ridge National Laboratory), Robert A. Bridges (Oak Ridge National Laboratory) and Michael D. Iannacone (Oak Ridge National Laboratory)

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ProvTalk: Towards Interpretable Multi-level Provenance Analysis in Networking Functions...

Azadeh Tabiban (CIISE, Concordia University, Montreal, QC, Canada), Heyang Zhao (CIISE, Concordia University, Montreal, QC, Canada), Yosr Jarraya (Ericsson Security Research, Ericsson Canada, Montreal, QC, Canada), Makan Pourzandi (Ericsson Security Research, Ericsson Canada, Montreal, QC, Canada), Mengyuan Zhang (Department of Computing, The Hong Kong Polytechnic University, China), Lingyu Wang (CIISE, Concordia University, Montreal, QC, Canada)

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