@inproceedings{4bcdd95b01124e87b1487376835bdfb6,
title = "Autonomous Driving System Configuration Defect Detection Method Based on Fuzzing",
abstract = "The configuration item values of each component within the autonomous driving system (ADS) are mutually constrained and complexly associated, which leads to problems such as configuration logic faults and memory overflow easily occurring during the configuration process, thus triggering the frequent occurrence of system configuration faults. This paper proposes a dynamic fuzzing method for configuration parameters based on static analysis of source code, through mapping and extracting configuration constraints within the system, realizing dynamic fuzzing for configuration parameters based on source code characterization, and completing the diagnosis of configuration defects and assistive repair functions. The experimental results show that the fuzzing method is effective in detecting and localizing configuration parameter defects under a variety of ADS anomalies, which not only dramatically improves the coverage rate of system configuration defect detection, but also achieves a configuration defect detection rate of 89.9%.",
keywords = "Autonomous Driving, Configuration Defects, Fuzzing, Static Analysis",
author = "Jinzhao Liu and Xiao Yu and Li Zhang and Yanqiu Zhang and Yuanzhang Li and Kun Tan and Yuan Tan",
note = "Publisher Copyright: {\textcopyright} ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.; 15th EAI International Conference on Digital Forensics and Cyber Crime, ICDF2C 2024 ; Conference date: 09-10-2024 Through 10-10-2024",
year = "2025",
doi = "10.1007/978-3-031-89360-5_18",
language = "English",
isbn = "9783031893599",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "296--312",
editor = "Sanjay Goel and Ersin Uzun and Mengjun Xie and Sumantra Sarkar",
booktitle = "Digital Forensics and Cyber Crime - 15th EAI International Conference, ICDF2C 2024, Proceedings",
address = "Germany",
}