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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LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors

Chengkun Wei (Zhejiang University), Wenlong Meng (Zhejiang University), Zhikun Zhang (CISPA Helmholtz Center for Information Security and Stanford University), Min Chen (CISPA Helmholtz Center for Information Security), Minghu Zhao (Zhejiang University), Wenjing Fang (Ant Group), Lei Wang (Ant Group), Zihui Zhang (Zhejiang University), Wenzhi Chen (Zhejiang University)

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Flow Correlation Attacks on Tor Onion Service Sessions with...

Daniela Lopes (INESC-ID / IST, Universidade de Lisboa), Jin-Dong Dong (Carnegie Mellon University), Pedro Medeiros (INESC-ID / IST, Universidade de Lisboa), Daniel Castro (INESC-ID / IST, Universidade de Lisboa), Diogo Barradas (University of Waterloo), Bernardo Portela (INESC TEC / Universidade do Porto), João Vinagre (INESC TEC / Universidade do Porto), Bernardo Ferreira (LASIGE, Faculdade de…

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Low-Quality Training Data Only? A Robust Framework for Detecting...

Yuqi Qing (Tsinghua University), Qilei Yin (Zhongguancun Laboratory), Xinhao Deng (Tsinghua University), Yihao Chen (Tsinghua University), Zhuotao Liu (Tsinghua University), Kun Sun (George Mason University), Ke Xu (Tsinghua University), Jia Zhang (Tsinghua University), Qi Li (Tsinghua University)

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