Gianluca Scopelliti (Ericsson & KU Leuven), Christoph Baumann (Ericsson), Fritz Alder (KU Leuven), Eddy Truyen (KU Leuven), Jan Tobias Mühlberg (Université libre de Bruxelles & KU Leuven)

In Intelligent Transport Systems, secure communication between vehicles, infrastructure, and other road users is critical to maintain road safety. This includes the revocation of cryptographic credentials of misbehaving or malicious vehicles in a timely manner. However, current standards are vague about how revocation should be handled, and recent surveys suggest severe limitations in the scalability and effectiveness of existing revocation schemes. In this paper, we present a formally verified mechanism for self-revocation of Vehicle-to-Everything (V2X) pseudonymous credentials, which relies on a trusted processing element in vehicles but does not require a trusted time source. Our scheme is compatible with ongoing standardization efforts and, leveraging the Tamarin prover, is the first to guarantee the actual revocation of credentials with a predictable upper bound on revocation time and in the presence of realistic attackers. We test our revocation mechanism in a virtual 5G-Edge deployment scenario where a large number of vehicles communicate with each other, simulating real-world conditions such as network malfunctions and delays. Results show that our scheme upholds formal guarantees in practice, while exhibiting low network overhead and good scalability.

View More Papers

MPCDiff: Testing and Repairing MPC-Hardened Deep Learning Models

Qi Pang (Carnegie Mellon University), Yuanyuan Yuan (HKUST), Shuai Wang (HKUST)

Read More

DeepGo: Predictive Directed Greybox Fuzzing

Peihong Lin (National University of Defense Technology), Pengfei Wang (National University of Defense Technology), Xu Zhou (National University of Defense Technology), Wei Xie (National University of Defense Technology), Gen Zhang (National University of Defense Technology), Kai Lu (National University of Defense Technology)

Read More

DeGPT: Optimizing Decompiler Output with LLM

Peiwei Hu (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Ruigang Liang (Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China), Kai Chen (Institute of Information Engineering, Chinese Academy of Sciences, China)

Read More

WIP: Security Vulnerabilities and Attack Scenarios in Smart Home...

Haoqiang Wang (Chinese Academy of Sciences, University of Chinese Academy of Sciences, Indiana University Bloomington), Yichen Liu (Indiana University Bloomington), Yiwei Fang, Ze Jin, Qixu Liu (Chinese Academy of Sciences, University of Chinese Academy of Sciences, Indiana University Bloomington), Luyi Xing (Indiana University Bloomington)

Read More