Feature-Guided Black-Box Safety Testing of Deep Neural Networks

21 October 2017

Papers citing "Feature-Guided Black-Box Safety Testing of Deep Neural Networks"

43 / 43 papers shown

Title
OSLO: One-Shot Label-Only Membership Inference Attacks Yuefeng Peng Jaechul Roh Subhransu Maji Amir Houmansadr 44 0 0 27 May 2024
When to Trust AI: Advances and Challenges for Certification of Neural Networks Marta Kwiatkowska Xiyue Zhang AAML 39 9 0 20 Sep 2023
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation Xiaowei Huang Wenjie Ruan Wei Huang Gao Jin Yizhen Dong ... Sihao Wu Peipei Xu Dengyu Wu André Freitas Mustafa A. Mustafa ALM 52 83 0 19 May 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 52 51 0 18 May 2023
Robust Explanation Constraints for Neural Networks Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 34 18 0 16 Dec 2022
Boosting Robustness Verification of Semantic Feature Neighborhoods Anan Kabaha Dana Drachsler-Cohen AAML 34 6 0 12 Sep 2022
Keep your Distance: Determining Sampling and Distance Thresholds in Machine Learning Monitoring Al-Harith Farhad Ioannis Sorokos Andreas Schmidt Mohammed Naveed Akram Koorosh Aslansefat Daniel Schneider 27 3 0 11 Jul 2022
Software Testing for Machine Learning D. Marijan A. Gotlieb AAML 24 27 0 30 Apr 2022
Excitement Surfeited Turns to Errors: Deep Learning Testing Framework Based on Excitable Neurons Haibo Jin Ruoxi Chen Haibin Zheng Jinyin Chen Yao Cheng Yue Yu Xianglong Liu AAML 33 6 0 12 Feb 2022
If a Human Can See It, So Should Your System: Reliability Requirements for Machine Vision Components Boyue Caroline Hu Lina Marsso Krzysztof Czarnecki Rick Salay Huakun Shen Marsha Chechik 24 21 0 08 Feb 2022
Security for Machine Learning-based Software Systems: a survey of threats, practices and challenges Huaming Chen Muhammad Ali Babar AAML 42 22 0 12 Jan 2022
Understanding and Measuring Robustness of Multimodal Learning Nishant Vishwamitra Hongxin Hu Ziming Zhao Long Cheng Feng Luo AAML 27 5 0 22 Dec 2021
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review Florian Tambon Gabriel Laberge Le An Amin Nikanjam Paulina Stevia Nouwou Mindom Y. Pequignot Foutse Khomh G. Antoniol E. Merlo François Laviolette 37 66 0 26 Jul 2021
Automatic Test Suite Generation for Key-Points Detection DNNs using Many-Objective Search (Experience Paper) Fitash Ul Haq Donghwan Shin Lionel C. Briand Thomas Stifter Jun Wang AAML 21 19 0 11 Dec 2020
Software engineering for artificial intelligence and machine learning software: A systematic literature review E. Nascimento Anh Nguyen-Duc Ingrid Sundbø T. Conte 18 40 0 07 Nov 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 32 73 0 07 Aug 2020
Global Robustness Verification Networks Weidi Sun Yuteng Lu Xiyue Zhang Zhanxing Zhu Meng Sun AAML 22 2 0 08 Jun 2020
A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems Anthony Corso Robert J. Moss Mark Koren Ritchie Lee Mykel J. Kochenderfer 19 173 0 06 May 2020
A Safety Framework for Critical Systems Utilising Deep Neural Networks Xingyu Zhao Alec Banks James Sharp Valentin Robu David Flynn Michael Fisher Xiaowei Huang AAML 55 48 0 07 Mar 2020
Robustness of Bayesian Neural Networks to Gradient-Based Attacks Ginevra Carbone Matthew Wicker Luca Laurenti A. Patané Luca Bortolussi G. Sanguinetti AAML 38 77 0 11 Feb 2020
Importance-Driven Deep Learning System Testing Simos Gerasimou Hasan Ferit Eniser A. Sen Alper Çakan AAML VLM 32 98 0 09 Feb 2020
ReluDiff: Differential Verification of Deep Neural Networks Brandon Paulsen Jingbo Wang Chao Wang 27 53 0 10 Jan 2020
DeepSmartFuzzer: Reward Guided Test Generation For Deep Learning Samet Demir Hasan Ferit Eniser A. Sen AAML 11 28 0 24 Nov 2019
Coverage Guided Testing for Recurrent Neural Networks Wei Huang Youcheng Sun Xing-E. Zhao James Sharp Wenjie Ruan Jie Meng Xiaowei Huang AAML 33 47 0 05 Nov 2019
Testing and verification of neural-network-based safety-critical control software: A systematic literature review Jin Zhang Jingyue Li 25 47 0 05 Oct 2019
A Systematic Mapping Study on Testing of Machine Learning Programs S. Sherin Muhammad Uzair Khan Muhammad Zohaib Z. Iqbal 30 13 0 11 Jul 2019
Machine Learning Testing: Survey, Landscapes and Horizons Jie M. Zhang Mark Harman Lei Ma Yang Liu VLM AILaw 39 741 0 19 Jun 2019
Taking Care of The Discretization Problem: A Comprehensive Study of the Discretization Problem and A Black-Box Adversarial Attack in Discrete Integer Domain Lei Bu Yuchao Duan Fu Song Zhe Zhao AAML 37 18 0 19 May 2019
Statistical Guarantees for the Robustness of Bayesian Neural Networks L. Cardelli Marta Kwiatkowska Luca Laurenti Nicola Paoletti A. Patané Matthew Wicker AAML 31 54 0 05 Mar 2019
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification Jianlin Li Pengfei Yang Jiangchao Liu Liqian Chen Xiaowei Huang Lijun Zhang AAML 24 80 0 26 Feb 2019
VERIFAI: A Toolkit for the Design and Analysis of Artificial Intelligence-Based Systems T. Dreossi Daniel J. Fremont Shromona Ghosh Edward J. Kim H. Ravanbakhsh Marcell Vazquez-Chanlatte S. Seshia 18 29 0 12 Feb 2019
Abduction-Based Explanations for Machine Learning Models Alexey Ignatiev Nina Narodytska Sasha Rubin FAtt 20 219 0 26 Nov 2018
Automated Test Generation to Detect Individual Discrimination in AI Models Aniya Aggarwal P. Lohia Seema Nagar Kuntal Dey Diptikalyan Saha 15 40 0 10 Sep 2018
DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing Xiaofei Xie Lei Ma Felix Juefei Xu Hongxu Chen Minhui Xue Bo-wen Li Yang Liu Jianjun Zhao Jianxiong Yin Simon See 43 40 0 04 Sep 2018
Using Machine Learning Safely in Automotive Software: An Assessment and Adaption of Software Process Requirements in ISO 26262 Rick Salay Krzysztof Czarnecki 25 69 0 05 Aug 2018
A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees Min Wu Matthew Wicker Wenjie Ruan Xiaowei Huang Marta Kwiatkowska AAML 19 111 0 10 Jul 2018
Automated Directed Fairness Testing Sakshi Udeshi Pryanshu Arora Sudipta Chattopadhyay FaML 6 170 0 02 Jul 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing Jingyi Wang Jun Sun Peixin Zhang Xinyu Wang AAML 21 41 0 14 May 2018
Concolic Testing for Deep Neural Networks Youcheng Sun Min Wu Wenjie Ruan Xiaowei Huang Marta Kwiatkowska Daniel Kroening 22 334 0 30 Apr 2018
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the $L_0$ Norm Wenjie Ruan Min Wu Youcheng Sun Xiaowei Huang Daniel Kroening Marta Kwiatkowska AAML 15 38 0 16 Apr 2018
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks D. Gopinath Guy Katz C. Păsăreanu Clark W. Barrett AAML 50 87 0 02 Oct 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 251 1,842 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 933 0 21 Oct 2016