Shuguang Wang (City University of Hong Kong), Qian Zhou (City University of Hong Kong), Kui Wu (University of Victoria), Jinghuai Deng (City University of Hong Kong), Dapeng Wu (City University of Hong Kong), Wei-Bin Lee (Information Security Center, Hon Hai Research Institute), Jianping Wang (City University of Hong Kong)

Autonomous driving systems (ADS) heavily depend on multi-sensor fusion (MSF) perception systems to process sensor data and improve the accuracy of environmental perception. However, MSF cannot completely eliminate uncertainties, and faults in multiple modules will lead to perception failures. Thus, identifying the root causes of these perception failures is crucial to ensure the reliability of MSF perception systems. Traditional methods for identifying perception failures, such as anomaly detection and runtime monitoring, are limited because they do not account for causal relationships between faults in multiple modules and overall system failure. To overcome these limitations, we propose a novel approach called interventional root cause analysis (IRCA). IRCA leverages the directed acyclic graph (DAG) structure of MSF to develop a hierarchical structural causal model (H-SCM), which effectively addresses the complexities of causal relationships. Our approach uses a divide-and-conquer pruning algorithm to encompass multiple causal modules within a causal path and to pinpoint intervention targets. We implement IRCA and evaluate its performance using real fault scenarios and synthetic scenarios with injected faults in the ADS Autoware. The average F1-score of IRCA in real fault scenarios is over $95%$. We also illustrate the effectiveness of IRCA on an autonomous vehicle testbed equipped with Autoware, as well as a cross-platform evaluation using Apollo. The results show that IRCA can efficiently identify the causal paths leading to failures and significantly enhance the safety of ADS.

View More Papers

PhantomLiDAR: Cross-modality Signal Injection Attacks against LiDAR

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

Read More

“Where Are We On Cyber?” – A Qualitative Study...

Jens Christian Opdenbusch (Ruhr University Bochum), Jonas Hielscher (Ruhr University Bochum), M. Angela Sasse (Ruhr University Bochum, University College London)

Read More

PowerRadio: Manipulate Sensor Measurement via Power GND Radiation

Yan Jiang (Zhejiang University), Xiaoyu Ji (Zhejiang University), Yancheng Jiang (Zhejiang University), Kai Wang (Zhejiang University), Chenren Xu (Peking University), Wenyuan Xu (Zhejiang University)

Read More

Revealing the Black Box of Device Search Engine: Scanning...

Mengying Wu (Fudan University), Geng Hong (Fudan University), Jinsong Chen (Fudan University), Qi Liu (Fudan University), Shujun Tang (QI-ANXIN Technology Research Institute; Tsinghua University), Youhao Li (QI-ANXIN Technology Research Institute), Baojun Liu (Tsinghua University), Haixin Duan (Tsinghua University; Quancheng Laboratory), Min Yang (Fudan University)

Read More