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Autonomous-Driving-Security-Resources

欢迎来到我的GitHub仓库，这里是一个专注于 自动驾驶安全 的知识库。自动驾驶技术正日益改变着我们的交通系统和出行方式，但与之同时，我们也必须关注和解决与自动驾驶相关的安全挑战。这个仓库的目标是收集和整理与自动驾驶安全相关的文献、研究论文、报告和资源，以帮助研究人员、工程师和社会大众更好地了解和探讨这一重要领域的问题。如果您有任何有关自动驾驶安全的文献或资源，欢迎贡献到这个仓库，让我们一起努力推动自动驾驶技术的安全发展。

CN doc EN doc

Contributing

Please feel free to send me pull requests to add links.

Table of Contents

Research Groups

Autonomous Driving Security

Autonomous Driving

  • 清华大学·车辆与运载学院·智能出行研究所 [link]
    • 李克强院士、杨殿阁、李升波等
  • 清华大学·智能产业研究院·AIR团队 [link]
    • 张亚勤院士等
  • 清华大学·交叉信息研究院·MARS Lab [link]
    • 赵行等
  • 北京大学·智能学院·智能车辆与移动机器人实验室 link]
    • 赵卉菁等
  • 北京理工大学·机械与车辆学院·车辆工程系 [link]
    • 陈慧岩、龚建伟、熊光明、倪俊等
  • 北京航空航天大学·交通科学与工程学院·交通运输工程系 [link]
    • 余贵珍、杨士春、于海洋等
  • 北京交通大学·计算机与信息技术学院·信息科学研究所 [link]
    • 赵耀、林春雨等
  • 西安交通大学·人工智能学院·人工智能与机器人研究所 [link]
    • 郑南宁院士等
  • 浙江大学·控制学院·智能驾驶与未来交通研究中心 [link]
    • 刘勇、冯冬芹等
  • 南京理工大学·自动化研究院/计算机学院·无人车团队 [link]
    • 任明武、杨静宇、石朝侠等
  • 同济大学·汽车学院·自主智能无人系统全国重点实验室/智能车辆与多智能体协同控制实验室/机器人与人工智能实验室（RAIL） [link]
    • 熊璐、朱西产、张皓等
  • 华中科技大学·人工智能与自动化学院 [link]
    • 王兴刚、何顶新等
  • 上海交通大学·机械与动力工程学院·智能汽车研究所/智能车实验室 [link]
    • 殷承良、杨明等

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Relevant Conferences

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Relevant Journals

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Relevant Competitions

Papers

Survey

  • Visually Adversarial Attacks and Defenses in the Physical World: A Survey. [pdf]

    • Xingxing Wei,Bangzheng Pu, Jiefan Lu, Baoyuan Wu. arXiv, 2023.

  • Recent Advancements in End-to-End Autonomous Driving using Deep Learning: A Survey. [pdf]

    • Pranav Singh Chib, Pravendra Singh. arXiv, 2023.

  • Deep learning for safe autonomous driving: Current challenges and future directions. [pdf]

    • Khan Muhammad, Amin Ullah, Jaime Lloret, Javier Del Ser, Victor Hugo C. de Albuquerque. IEEE Transactions on Intelligent Transportation Systems, 2021.

  • Deep learning-based autonomous driving systems: A survey of attacks and defenses. [pdf]

    • Yao Deng, Tiehua Zhang, Guannan Lou, Xi Zheng, Jiong Jin, Qing-Long Han. IEEE Transactions on Industrial Informatics, 2021.

  • Autonomous driving security: State of the art and challenges. [pdf]

    • Cong Gao, Geng Wang, Weisong Shi, Zhongmin Wang, Yanping Chen. IEEE Internet of Things Journal, 2021.

Camera Attack and Defense

  • Attacking vision-based perception in end-to-end autonomous driving models. [pdf] [code]
    • Adith Boloor, Karthik Garimella, Xin He, Christopher Gill, Yevgeniy Vorobeychik, Xuan Zhang. Journal of Systems Architecture, 2020.

Lane Detection Attack and Defense

  • Lateral-Direction Localization Attack in High-Level Autonomous Driving: Domain-Specific Defense Opportunity via Lane Detection. [pdf]

    • Junjie Shen, Yunpeng Luo, Ziwen Wan, Qi Alfred Chen. arXiv, 2023.

  • Physical Backdoor Attacks to Lane Detection Systems in Autonomous Driving. [pdf] [note]

    • Xingshuo Han, Guowen Xu, Yuan Zhou*, Xuehuan Yang, Jiawei Li, Tianwei Zhang. ACM International Conference on Multimedia, 2022.

  • Too Good to Be Safe: Tricking Lane Detection in Autonomous Driving with Crafted Perturbations. [pdf]

    • Pengfei Jing, Qiyi Tang, Yuefeng Du, Lei Xue, Xiapu Luo, Ting Wang, Sen Nie, Shi Wu. Usenix Security, 2021.

  • Dirty Road Can Attack: Security of Deep Learning based Automated Lane Centering under Physical-World Attack. [pdf]

    • Takami Sato, Junjie Shen, Ningfei Wang, Yunhan Jia, Xue Lin, Qi Alfred Chen. Usenix Security, 2021.

LiDAR Attack and Defense

  • You Can't See Me: Physical Removal Attacks on LiDAR-based Autonomous Vehicles Driving Frameworks. [pdf]
    • Yulong Cao, S. Hrushikesh Bhupathiraju, Pirouz Naghavi, Takeshi Sugawara, Z. Morley Mao*, Sara Rampazzi. Usenix Security, 2023.
  • Who Is in Control? Practical Physical Layer Attack and Defense for mmWave-Based Sensing in Autonomous Vehicles. [pdf]
    • Zhi Sun, Sarankumar Balakrishnan, Lu Su, Arupjyoti Bhuyan, Pu Wang, Chunming Qiao. IEEE Transactions on Information Forensics and Security (TIFS) 2021.

Multi-Sensor Fusion Attack and Defense

  • Security Analysis of {Camera-LiDAR} Fusion Against {Black-Box} Attacks on Autonomous Vehicles. [pdf]

    • R. Spencer Hallyburton, Yupei Liu, Yulong Cao, Z. Morley Mao, Miroslav Pajic. Usenix Security, 2022.

  • Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks. [pdf]

    • Yulong Cao, Ningfei Wang, Chaowei Xiao, Dawei Yang, Jin Fang, Ruigang Yang, Qi Alfred Chen, Mingyan Liu, Bo Li. S&P, 2021.

Trajectory Prediction Attack and Defense

  • Vehicle Trajectory Prediction Works, but Not Everywhere. [pdf]
    • Mohammadhossein Bahari, Saeed Saadatnejad, Ahmad Rahimi, Mohammad Shaverdikondori, Amir Hossein Shahidzadeh, Seyed-Mohsen Moosavi-Dezfooli, Alexandre Alahi. CVPR 2022.

System Testing

  • Mind the gap! a study on the transferability of virtual vs physical-world testing of autonomous driving systems. [pdf]
    • Andrea Stocco, Brian Pulfer, Paolo Tonella. IEEE Transactions on Software Engineering (TSE), 2022.
  • DriveFuzz: Discovering Autonomous Driving Bugs through Driving Quality-Guided Fuzzing.
  • Testing the safety of self-driving vehicles by simulating perception and prediction. [pdf]
    • Kelvin Wong, Qiang Zhang, Ming Liang, Bin Yang, Renjie Liao, Abbas Sadat & Raquel Urtasun. ECCV, 2020.
  • AV-FUZZER: Finding Safety Violations in Autonomous Driving Systems. [pdf]
    • International Symposium on Software Reliability Engineering (ISSRE), 2020.
  • Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios. [pdf]
    • Baiming Chen, Xiang Chen, Qiong Wu, Liang Li. IEEE Transactions on Intelligent Transportation Systems (TITS), 2021.
  • DeepRoad: GAN-based Metamorphic Testing and Input Validation Framework for Autonomous Driving Systems. [pdf]
    • MengshiZhang, Yuqun Zhang, Lingming Zhang, Cong Liu, Sarfraz Khurshid. International Conference on Automated Software Engineering (ASE), 2018.
  • DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars. [pdf]
    • Yuchi Tian, Kexin Pei, Suman Jana, Baishakhi Ray. International Conference on Software Engineering (ICSE), 2018.
  • Systematic Testing of Convolutional Neural Networks for Autonomous Driving. [pdf]
    • Tommaso Dreossi, Shromona Ghosh, Alberto Sangiovanni-Vincentelli, Sanjit A. Seshia. arXiv, 2017.

Scenario Generation

  • A survey on safety-critical driving scenario generation—A methodological perspective. [pdf]

    • Wenhao Ding, Chejian Xu, Mansur Arief, Haohong Lin, Bo Li, Ding Zhao. IEEE Transactions on Intelligent Transportation Systems (TITS), 2023.

  • Online Adaptive Generation of Critical Boundary Scenarios for Evaluation of Autonomous Vehicles. [pdf]

    • Junjie Zhou, Lin Wang, Xiaofan Wang. IEEE Transactions on Intelligent Transportation Systems (TITS), 2023.

  • SceGene: Bio-Inspired Traffic Scenario Generation for Autonomous Driving Testing. [pdf]

    • Ao Li, Shitao Chen, Liting Sun, Nanning Zheng, Masayoshi Tomizuka, Wei Zhan. IEEE Transactions on Intelligent Transportation Systems (TITS), 2022.

  • Test Scenario Generation and Optimization Technology for Intelligent Driving Systems. [pdf]

    • Jianli Duan, Feng Gao, Yingdong He. IEEE Intelligent Transportation Systems Magazine, 2020.

  • Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method. [pdf]

    • Wenhao Ding, Baiming Chen, Minjun Xu, Ding Zhao. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.

Anomaly Detection

  • Detecting the Anomalies in LiDAR Pointcloud. [pdf]
    • Chiyu Zhang, Ji Han, Yao Zou, Kexin Dong, Yujia Li, Junchun Ding, Xiaoling Han. arXiv, 2023.

End to End

  • Adversarial Driving: Attacking End-to-End Autonomous Driving. [pdf]
    • Han Wu, Syed Yunas, Sareh Rowlands, Wenjie Ruan, Johan Wahlström. IEEE Intelligent Vehicles Symposium, 2023.

Other

  • Reasoning about Safety of Learning-Enabled Components in Autonomous Cyber-physical Systems. [pdf]
    • Cumhur Erkan Tuncali, James Kapinski, Hisahiro Ito, Jyotirmoy V. Deshmukh. Annual Design Automation Conference, 2018.

Datasets

  • AmodalSynthDrive: A Synthetic Amodal Perception Dataset for Autonomous Driving. [pdf]

    • Ahmed Rida Sekkat, Rohit Mohan, Oliver Sawade, Elmar Matthes, Abhinav Valada. arXiv, 2023.

  • ADD: An Automatic Desensitization Fisheye Dataset for Autonomous Driving. [pdf]

    • Zizhang Wu, Xinyuan Chen, Hongyang Wei, Fan Song, Tianhao Xua. arXiv, 2023.

  • SUPS: A Simulated Underground Parking Scenario Dataset for Autonomous Driving. [pdf]

    • Jiawei Hou, Qi Chen, Yurong Cheng, Guang Chen, Xiangyang Xue, Taiping Zeng, Jian Pu*. arXiv, 2023.

  • A Survey on Datasets for Decision-making of Autonomous Vehicle. [pdf]

    • Yuning Wang, Zeyu Han, Yining Xing, Shaobing Xu*, Jianqiang Wang*. arXiv, 2023.

  • CityPersons: A Diverse Dataset for Pedestrian Detection. [pdf]

    • Shanshan Zhang, Rodrigo Benenson, Bernt Schiele. CVPR, 2017.

  • Are we ready for autonomous driving? The KITTI vision benchmark suite. [pdf]

    • Andreas Geiger, Philip Lenz, Raquel Urtasun. CVPR, 2012.