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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MOCK: Optimizing Kernel Fuzzing Mutation with Context-aware Dependency

Jiacheng Xu (Zhejiang University), Xuhong Zhang (Zhejiang University), Shouling Ji (Zhejiang University), Yuan Tian (UCLA), Binbin Zhao (Georgia Institute of Technology), Qinying Wang (Zhejiang University), Peng Cheng (Zhejiang University), Jiming Chen (Zhejiang University)

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Predictive Context-sensitive Fuzzing

Pietro Borrello (Sapienza University of Rome), Andrea Fioraldi (EURECOM), Daniele Cono D'Elia (Sapienza University of Rome), Davide Balzarotti (Eurecom), Leonardo Querzoni (Sapienza University of Rome), Cristiano Giuffrida (Vrije Universiteit Amsterdam)

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REPLICAWATCHER: Training-less Anomaly Detection in Containerized Microservices

Asbat El Khairi (University of Twente), Marco Caselli (Siemens AG), Andreas Peter (University of Oldenburg), Andrea Continella (University of Twente)

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