Zizhi Jin (Zhejiang University), Qinhong Jiang (Zhejiang University), Xuancun Lu (Zhejiang University), Chen Yan (Zhejiang University), Xiaoyu Ji (Zhejiang University), Wenyuan Xu (Zhejiang University)

LiDAR (Light Detection and Ranging) is a pivotal sensor for autonomous driving, offering precise 3D spatial information.
Previous signal attacks against LiDAR systems mainly exploit laser signals. In this paper, we investigate the possibility of cross-modality signal injection attacks, i.e., injecting intentional electromagnetic interference (IEMI) to manipulate LiDAR output. Our insight is that the internal modules of a LiDAR, i.e., the laser receiving circuit, the monitoring sensors, and the beam-steering modules, even with strict electromagnetic compatibility (EMC) testing, can still couple with the IEMI attack signals and result in the malfunction of LiDAR systems. Based on the above attack surfaces, we propose the alias attack, which manipulates LiDAR output in terms of textit{Points Interference}, textit{Points Injection}, textit{Points Removal}, and even textit{LiDAR Power-Off}.
We evaluate and demonstrate the effectiveness of alias with both simulated and real-world experiments on five COTS LiDAR systems.
We also conduct feasibility experiments in real-world moving scenarios.
We provide potential defense measures that can be implemented at both the sensor level and the vehicle system level to mitigate the risks associated with IEMI attacks. Video demonstrations can be viewed at textcolor{blue}{href{https://sites.google.com/view/phantomlidar}{https://sites.google.com/view/phantomlidar}}.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 118 ) ) ) [post__not_in] => Array ( [0] => 20182 ) )

SecuWear: Secure Data Sharing Between Wearable Devices

Sujin Han (KAIST) Diana A. Vasile (Nokia Bell Labs), Fahim Kawsar (Nokia Bell Labs, University of Glasgow), Chulhong Min (Nokia Bell Labs)

Read More

Attributing Open-Source Contributions is Critical but Difficult: A Systematic...

Jan-Ulrich Holtgrave (CISPA Helmholtz Center for Information Security), Kay Friedrich (CISPA Helmholtz Center for Information Security), Fabian Fischer (CISPA Helmholtz Center for Information Security), Nicolas Huaman (Leibniz University Hannover), Niklas Busch (CISPA Helmholtz Center for Information Security), Jan H. Klemmer (CISPA Helmholtz Center for Information Security), Marcel Fourné (Paderborn University), Oliver Wiese (CISPA Helmholtz Center…

Read More

AI-Assisted RF Fingerprinting for Identification of User Devices in...

Aishwarya Jawne (Center for Connected Autonomy & AI, Florida Atlantic University), Georgios Sklivanitis (Center for Connected Autonomy & AI, Florida Atlantic University), Dimitris A. Pados (Center for Connected Autonomy & AI, Florida Atlantic University), Elizabeth Serena Bentley (Air Force Research Laboratory)

Read More

CASPR: Context-Aware Security Policy Recommendation

Lifang Xiao (Institute of Information Engineering, Chinese Academy of Sciences), Hanyu Wang (Institute of Information Engineering, Chinese Academy of Sciences), Aimin Yu (Institute of Information Engineering, Chinese Academy of Sciences), Lixin Zhao (Institute of Information Engineering, Chinese Academy of Sciences), Dan Meng (Institute of Information Engineering, Chinese Academy of Sciences)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)