Evan Allen (Virginia Tech), Zeb Bowden (Virginia Tech Transportation Institute), Randy Marchany (Virginia Tech), J. Scot Ransbottom (Virginia Tech)

Modern vehicles are increasingly connected systems that expose a wide variety of security risks to their users. Message authentication prevents entire classes of these attacks, such as message spoofing and electronic control unit impersonation, but current in-vehicle networks do not include message authentication features. Latency and throughput requirements for vehicle traffic can be very stringent (100 Mbps in cases), making it difficult to implement message authentication with cryptography due to the overheads required. This work investigates the feasibility of implementing cryptography-based message authentication in Automotive Ethernet networks that is fast enough to comply with these performance requirements. We find that it is infeasible to include Message Authentication Codes in all traffic without costly hardware accelerators and propose an alternate approach for future research to minimize the cost of authenticated traffic.

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AuthentiSense: A Scalable Behavioral Biometrics Authentication Scheme using Few-Shot...

Hossein Fereidooni (Technical University of Darmstadt), Jan Koenig (University of Wuerzburg), Phillip Rieger (Technical University of Darmstadt), Marco Chilese (Technical University of Darmstadt), Bora Goekbakan (KOBIL, Germany), Moritz Finke (University of Wuerzburg), Alexandra Dmitrienko (University of Wuerzburg), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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Parakeet: Practical Key Transparency for End-to-End Encrypted Messaging

Harjasleen Malvai (UIUC/IC3), Lefteris Kokoris-Kogias (IST Austria), Alberto Sonnino (Mysten Labs), Esha Ghosh (Microsoft Research), Ercan Oztürk (Meta), Kevin Lewi (Meta), Sean Lawlor (Meta)

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VICEROY: GDPR-/CCPA-compliant Enforcement of Verifiable Accountless Consumer Requests

Scott Jordan (University of California, Irvine), Yoshimichi Nakatsuka (University of California, Irvine), Ercan Ozturk (University of California, Irvine), Andrew Paverd (Microsoft Research), Gene Tsudik (University of California, Irvine)

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Fusion: Efficient and Secure Inference Resilient to Malicious Servers

Caiqin Dong (Jinan University), Jian Weng (Jinan University), Jia-Nan Liu (Jinan University), Yue Zhang (Jinan University), Yao Tong (Guangzhou Fongwell Data Limited Company), Anjia Yang (Jinan University), Yudan Cheng (Jinan University), Shun Hu (Jinan University)

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