The complexity of vehicle cybersecurity seems to be increasing at an ever-accelerating pace. With the electrification of transportation, the adoption of AI, and new regulations and standards, “secure by design” seems to be moving out of reach. How can we navigate this complex realm and make actual progress? What does the industry need to focus on? What can academia do to help advance the state of the possible? Join us as we explore some answers to these important questions.

Speaker's Biography: Urban conducted some of the first research into heavy vehicle cybersecurity in 2014 and wrote one of the first papers on the subject in 2015. While at NMFTA, Urban founded and ran the heavy vehicle cybersecurity / commercial transportation security and research program. With over thirty-five years of experience, Urban is a hands-on technologist and leader. He has a successful track record of understanding, analyzing, mapping, and providing solutions for complex systems. Urban maintains several vehicle cybersecurity advisory roles, including technical support to SAE International standards committees, a Technology & Maintenance Council (TMC) S.5 and S.12 Study Group Member, ESCAR USA Conference Program Committee, CyberTruck Challenge Board Member and Speaker, and a Transportation Cybersecurity Subject Matter Expert for FBI InfraGard and FBI Automotive Sector Specific Working Group.

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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)

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EM Eye: Characterizing Electromagnetic Side-channel Eavesdropping on Embedded Cameras

Yan Long (University of Michigan), Qinhong Jiang (Zhejiang University), Chen Yan (Zhejiang University), Tobias Alam (University of Michigan), Xiaoyu Ji (Zhejiang University), Wenyuan Xu (Zhejiang University), Kevin Fu (Northeastern University)

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ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learning

Linkang Du (Zhejiang University), Min Chen (CISPA Helmholtz Center for Information Security), Mingyang Sun (Zhejiang University), Shouling Ji (Zhejiang University), Peng Cheng (Zhejiang University), Jiming Chen (Zhejiang University), Zhikun Zhang (CISPA Helmholtz Center for Information Security and Stanford University)

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WIP: Augmenting Vehicle Safety With Passive BLE

Noah T. Curran (University of Michigan), Kang G. Shin (University of Michigan), William Hass (Lear Corporation), Lars Wolleschensky (Lear Corporation), Rekha Singoria (Lear Corporation), Isaac Snellgrove (Lear Corporation), Ran Tao (Lear Corporation)

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