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title
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Zelun Kong
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2026-02-26 09:43:05
raw text
DriveFuzz: Feedback-Driven Fuzzing for Autonomous Driving Systems Software & Systems Security Laboratory (S3 Lab) Introduction Demo Installation & Run Results Cite DriveFuzz DriveFuzz is a feedback-driven fuzzing framework for testing autonomous driving systems end-to-end, which automatically generates safety-critical driving scenarios in which an autonomous driving system misbehaves. DriveFuzz: Discovering Autonomous Driving Bugs through Driving Quality-Guided Fuzzing . Seulbae Kim, Major Liu, Junghwan "John" Rhee, Yuseok Jeon, Yonghwi Kwon, Chung Hwan Kim. In Proceedings of the 29th ACM Conference on Computer and Communications Security ( CCS 2022 ) , Los Angeles, CA, November 2022. Fork me on GitLab! YouTube Channel Paper Extended Paper Introduction Autonomous driving systems (ADS) are steadily becoming a reality, and we expect them to be safer than human drivers. Unfortunately, we continue ...
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