APSEC 2024
Tue 3 - Fri 6 December 2024 China

This program is tentative and subject to change.

Wed 4 Dec 2024 17:00 - 17:30 at Room 2 (Xiangshan Ballroom) - Session (5)

Autonomous Driving Systems (ADS) hold significant potential for enhancing travel convenience. Ensuring the reliability of ADS through efficient and comprehensive simulation testing has garnered substantial attention from researchers. In recent years, various search-based automated test scenario generation methods have been proposed to identify potential ADS defects. However, these methods still face challenges in balancing efficiency with comprehensive testing and suffer from a lack of diversity. To address these challenges, we propose AS-Fuzzer, an optimized ADS fuzzing method based on composite traffic scenario generation. AS-Fuzzer introduces a scenario slicing technique based on traffic road structures, allowing each sliced scenario to evolve independently and in parallel, enhancing interaction rates and balancing efficiency with comprehensive testing. A novel scenario generation method CEGA, is applied within AS-Fuzzer to improve the diversity of generated scenarios, thereby exploring a wider range of ADS defects. Experimental results demonstrate that the proposed method improves test scenario generation efficiency by 120% compared to the state-of-the-art baseline method. Additionally, in the simulation testing of the proposed method, the interaction rate between the ADS vehicle and non-player characters is 2.79 times that of the baseline method, thereby further enhancing ADS testing efficiency. Furthermore, within the same time frame, the proposed method uncovered 19 types of ADS defects that other baseline methods did not explore, achieving higher ADS defect diversity.

This program is tentative and subject to change.

Wed 4 Dec

Displayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change

16:00 - 17:30
16:00
30m
Talk
SwFuzz: Structure-Sensitive WebAssembly Fuzzing
Technical Track
Jiashui Wang Zhejiang University, Ziyi Guo Northwestern University, Xinlei Ying Ant Group, Peng Qian Zhejiang University, Yan Chen Northwestern University
16:30
30m
Talk
Data Conflicts-Guided Interleaved Thread Scheduling for Flaky Test Detection in Multithreaded Programs
Technical Track
Tianzi Wang College of lnformation Science and Technology, Beijing University of chemical Technology, Beijing, China, Ruilian Zhao Beijing University of Chemical Technology, Weiwei Wang College of lnformation Science and Technology, Beijing University of chemical Technology, Beijing, China, Weixi Zhang College of Information Engineering, Beijing Institute of Petrochemical Technology, Beijing, China
17:00
30m
Talk
AS-Fuzzer: An Optimized ADS Fuzzing Method via Scenario Segmentation and Parallel Evolution
Technical Track
Fansong Chen Institute of Information Engineering, Chinese Academy of Sciences, Shenghao Lin Institute of Information Engineering, Chinese Academy of Sciences, Weicheng Lin Institute of Information Engineering, Chinese Academy of Sciences, Laile Xi Institute of Information Engineering, Chinese Academy of Sciences , Yongji Liu Institute of Information Engineering, Chinese Academy of Sciences, Lun Li Institute of Information Engineering at Chinese Academy of Sciences, Hongsong Zhu Institute of Information Engineering at Chinese Academy of Sciences; University of Chinese Academy of Sciences