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.

View More Papers

VETEOS: Statically Vetting EOSIO Contracts for the “Groundhog Day”...

Levi Taiji Li (University of Utah), Ningyu He (Peking University), Haoyu Wang (Huazhong University of Science and Technology), Mu Zhang (University of Utah)

Read More

Front-running Attack in Sharded Blockchains and Fair Cross-shard Consensus

Jianting Zhang (Purdue University), Wuhui Chen (Sun Yat-sen University), Sifu Luo (Sun Yat-sen University), Tiantian Gong (Purdue University), Zicong Hong (The Hong Kong Polytechnic University), Aniket Kate (Purdue University)

Read More

AVMON: Securing Autonomous Vehicles by Learning Control Invariants and...

Ahmed Abdo, Sakib Md Bin Malek, Xuanpeng Zhao, Nael Abu-Ghazaleh (University of California, Riverside)

Read More

FP-Fed: Privacy-Preserving Federated Detection of Browser Fingerprinting

Meenatchi Sundaram Muthu Selva Annamalai (University College London), Igor Bilogrevic (Google), Emiliano De Cristofaro (University of California, Riverside)

Read More