D-SLAMSpoof: 動的点群注入による環境非依存のLiDARスプーフィング攻撃
D-SLAMSpoof: An Environment-Agnostic LiDAR Spoofing Attack using Dynamic Point Cloud Injection
LiDAR SLAMに対する新たな攻撃手法D-SLAMSpoofを提案し、特徴豊かな環境でも攻撃を成功させる。また、慣性航法のみを用いた防御手法ISD-SLAMも提案し、その有効性を示した。
詳しい要約
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2. 先行研究と比べてどこがすごい？
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著者: Rokuto Nagata, Kenji Koide, Kazuma Ikeda, Ozora Sako, Kentaro Yoshioka
分類: cs.RO
原文アブストラクト
In this work, we introduce Dynamic SLAMSpoof (D-SLAMSpoof), a novel attack that compromises LiDAR SLAM even in feature-rich environments. The attack leverages LiDAR spoofing, which injects spurious measurements into LiDAR scans through external laser interference. By designing both spatial injection shapes and temporally coordinated dynamic injection patterns guided by scan-matching principles, D-SLAMSpoof significantly improves attack success rates in real-world, feature-rich environments such as urban areas and indoor spaces, where conventional LiDAR spoofing methods often fail. Furthermore, we propose a practical defense method, ISD-SLAM, that relies solely on inertial dead reckoning signals commonly available in autonomous systems. We demonstrate that ISD-SLAM accurately detects LiDAR spoofing attacks, including D-SLAMSpoof, and effectively mitigates the resulting position drift. Our findings expose inherent vulnerabilities in LiDAR-based SLAM and introduce the first practical defense against LiDAR-based SLAM spoofing using only standard onboard sensors, providing critical insights for improving the security and reliability of autonomous systems.
