DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in
Neural Networks

DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks

2 October 2017

Clark W. Barrett

Papers citing "DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks"

18 / 18 papers shown

Title
A Survey of Neural Network Robustness Assessment in Image Recognition Jie Wang Jun Ai Minyan Lu Haoran Su Dan Yu Yutao Zhang Junda Zhu Jingyu Liu AAML 30 3 0 12 Apr 2024
Closed-loop Analysis of Vision-based Autonomous Systems: A Case Study C. Păsăreanu Ravi Mangal D. Gopinath Sinem Getir Yaman Calum Imrie R. Calinescu Huafeng Yu 32 29 0 06 Feb 2023
Verification-Aided Deep Ensemble Selection Guy Amir Tom Zelazny Guy Katz Michael Schapira AAML 30 18 0 08 Feb 2022
Minimal Multi-Layer Modifications of Deep Neural Networks Idan Refaeli Guy Katz KELM AAML 35 15 0 18 Oct 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 34 66 0 26 Jul 2021
Adversarial Ranking Attack and Defense Mo Zhou Zhenxing Niu Le Wang Qilin Zhang G. Hua 36 38 0 26 Feb 2020
Importance-Driven Deep Learning System Testing Simos Gerasimou Hasan Ferit Eniser A. Sen Alper Çakan AAML VLM 30 98 0 09 Feb 2020
An Abstraction-Based Framework for Neural Network Verification Y. Elboher Justin Emile Gottschlich Guy Katz 27 122 0 31 Oct 2019
Simplifying Neural Networks using Formal Verification S. Gokulanathan Alexander Feldsher Adi Malca Clark W. Barrett Guy Katz 33 4 0 25 Oct 2019
Formal Verification of Decision-Tree Ensemble Model and Detection of its Violating-input-value Ranges Naoto Sato Hironobu Kuruma Y. Nakagawa H. Ogawa 22 12 0 26 Apr 2019
DeepSaucer: Unified Environment for Verifying Deep Neural Networks Naoto Sato Duong Nguyen Anh M. Kaneko Yuichiroh Nakagawa H. Ogawa Son Hoang Michael J. Butler 13 1 0 09 Nov 2018
DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing Xiaofei Xie L. 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
A Game-Based Approximate Verification of Deep Neural Networks with Provable Guarantees Min Wu Matthew Wicker Wenjie Ruan Xiaowei Huang Marta Kwiatkowska AAML 16 111 0 10 Jul 2018
Automated Verification of Neural Networks: Advances, Challenges and Perspectives Francesco Leofante Nina Narodytska Luca Pulina A. Tacchella AAML 12 69 0 25 May 2018
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 249 1,838 0 03 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 296 3,112 0 04 Nov 2016
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,842 0 08 Jul 2016