Michele Marazzi, Stefano Longari, Michele Carminati, Stefano Zanero (Politecnico di Milano)

ZOOX AutoDriving Security Award Runner-up!

With the increasing interest in autonomous vehicles (AVs), ensuring their safety and security is becoming crucial. The introduction of advanced features has increased the need for various interfaces to communicate with the external world, creating new potential attack vectors that attackers can exploit to alter sensor data. LiDAR sensors are widely employed to support autonomous driving features and generate point cloud data used by ADAS to 3D map the vehicle’s surroundings. Tampering attacks on LiDAR-generated data can compromise the vehicle’s functionalities and seriously threaten passengers and other road users. Existing approaches to LiDAR data tampering detection show security flaws and can be bypassed by attackers through design vulnerabilities. This paper proposes a novel approach for tampering detection of LiDAR-generated data in AVs, employing a watermarking technique. We validate our approach through experiments to prove its feasibility in realworld time-constrained scenarios and its efficacy in detecting LiDAR tampering attacks. Our approach performs better when compared to the current state-of-the-art LiDAR watermarking techniques while addressing critical issues related to watermark security and imperceptibility.

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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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Sticky Fingers: Resilience of Satellite Fingerprinting against Jamming Attacks

Joshua Smailes (University of Oxford), Edd Salkield (University of Oxford), Sebastian Köhler (University of Oxford), Simon Birnbach (University of Oxford), Martin Strohmeier (Cyber-Defence Campus, armasuisse S+T), Ivan Martinovic (University of Oxford)

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Dongyao Chen (Shanghai Jiao Tong University), Mert D. Pesé (Clemson University), Kang G. Shin (University of Michigan, Ann Arbor)

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Efficient and Timely Revocation of V2X Credentials

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)

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