Autonomous-Driving-Security-Resources

🚗 A repository for documenting and exploring the world of autonomous driving safety, featuring a curated collection of research groups, conferences, journals, competitions, papers, reports, and resource. Inspired by awesome-php.

Contributing

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

Table of Contents

• Foundations
• Revelant Repositories
• Research Labs
• Relevant Conferences
• Relevant Journals
• Relevant Competitions
• Papers

Foundations

• Artificial Intelligence

  • Awesome Machine Learning - A curated list of awesome Machine Learning frameworks, libraries and software. Maintained by Joseph Misiti.Joseph Misiti
  • Deep Learning Papers Reading Roadmap - Deep Learning papers reading roadmap constructed from outline to detail, old to state-of-the-art, from generic to specific areas focus on state-of-the-art for anyone starting in Deep Learning. Maintained by, Flood Sung.
  • Open Source Deep Learning Curriculum - Deep Learning curriculum meant to be a starting point for everyone interested in seriously studying the field.

• Robotics

  • Awesome Robotics - A list of various books, courses and other resources for robotics, maintained by kiloreux.

• Computer Vision

  • Awesome Computer Vision - A curated list of awesome computer vision resources, maintained by Jia-Bin Huang
  • Awesome Deep Vision - A curated list of deep learning resources for computer vision, maintained by Jiwon Kim, Heesoo Myeong, Myungsub Choi, Jung Kwon Lee, Taeksoo Kim

Revelant Repositories

• Autonomous Driving Cookbook - Scenarios, tutorials and demos for Autonomous Driving.
• Slam in Autonomous Driving - SLAM Technology in Autonomous Driving corresponds to open source code.
• SensorsCalibration - A Multi-sensor Calibration Toolbox for Autonomous Driving.

Research Labs

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Relevant Conferences

• Security

  • ACM Conference on Computer and Communications Security (CCS) - CCF-A
  • Network and Distributed System Security Symposium (NDSS) - CCF-A
  • IEEE Symposium on Security and Privacy (S&P) - CCF-A
  • USENIX Security Symposium - CCF-A

• Artificial Intelligence & Computer Vision

  • Computer Vision and Pattern Recognition (CVPR) - CCF-A
  • IEEE International Conference on Computer Vision (ICCV) - CCF-A
  • European Conference on Computer Vision (ECCV) - CCF-B

• Software Engineering

  • International Conference on Automated Software Engineering (ASE) - CCF-A
  • International Conference on Software Engineering (ICSE) - CCF-A
  • International Symposium on Software Testing and Analysis (ISSTA) - CCF-A

• Multimedia

  • ACM International Conference on Multimedia (ACM MM) - CCF-A

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Relevant Journals

• IEEE Transactions on Information Forensics and Security (TIFS) - CCF-B / JCR Q1
• IEEE Transactions on Intelligent Transportation Systems (TITS) - CCF-B / JCR Q1
• IEEE Transactions on Intelligent Vehicles (TIV) - JCR Q1
• IEEE Transactions on Vehicular Technology (TVT) - JCR Q2
• IEEE Transactions on Reliability (TR) - CCF-C / JCR Q2

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Relevant Competitions

• World Intelligent Driving Challenge, WIDC
• China International Autopilot Challenge, CIAC
• Intelligent Vehicle Future Challenge, IVFC
• Kaggle
• Tianchi

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Papers

• Survey
• Scenario Generation
• Datasets
• Perception

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.