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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Efficient Privacy-Preserved Processing of Multimodal Data for Vehicular Traffic...

Meisam Mohammady (Iowa State University), Reza Arablouei (Data61, CSIRO)

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CrowdGuard: Federated Backdoor Detection in Federated Learning

Phillip Rieger (Technical University of Darmstadt), Torsten Krauß (University of Würzburg), Markus Miettinen (Technical University of Darmstadt), Alexandra Dmitrienko (University of Würzburg), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

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CAGE: Complementing Arm CCA with GPU Extensions

Chenxu Wang (Southern University of Science and Technology (SUSTech) and The Hong Kong Polytechnic University), Fengwei Zhang (Southern University of Science and Technology (SUSTech)), Yunjie Deng (Southern University of Science and Technology (SUSTech)), Kevin Leach (Vanderbilt University), Jiannong Cao (The Hong Kong Polytechnic University), Zhenyu Ning (Hunan University), Shoumeng Yan (Ant Group), Zhengyu He (Ant…

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EMMasker: EM Obfuscation Against Website Fingerprinting

Mohammed Aldeen, Sisheng Liang, Zhenkai Zhang, Linke Guo (Clemson University), Zheng Song (University of Michigan – Dearborn), and Long Cheng (Clemson University)

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