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A Survey of Neural Network Robustness Assessment in Image Recognition

12 April 2024

Papers citing "A Survey of Neural Network Robustness Assessment in Image Recognition"

50 / 70 papers shown

Title
Verification of Neural Networks' Global Robustness Anan Kabaha Dana Drachsler-Cohen AAML OOD 58 6 0 29 Feb 2024
A Survey of Robustness and Safety of 2D and 3D Deep Learning Models Against Adversarial Attacks Yanjie Li Bin Xie Songtao Guo Yuanyuan Yang Bin Xiao AAML 78 18 0 01 Oct 2023
Using Z3 for Formal Modeling and Verification of FNN Global Robustness Yihao Zhang Zeming Wei Xiyue Zhang Meng Sun AAML 53 6 0 20 Apr 2023
Asymmetric Certified Robustness via Feature-Convex Neural Networks Samuel Pfrommer Brendon G. Anderson Julien Piet Somayeh Sojoudi AAML 60 8 0 03 Feb 2023
QVIP: An ILP-based Formal Verification Approach for Quantized Neural Networks Yedi Zhang Zhe Zhao Fu Song Hao Fei Tao Chen Jun Sun 54 17 0 10 Dec 2022
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches Maura Pintor Daniele Angioni Angelo Sotgiu Christian Scano Ambra Demontis Battista Biggio Fabio Roli AAML 87 53 0 07 Mar 2022
A Review of Adversarial Attack and Defense for Classification Methods Yao Li Minhao Cheng Cho-Jui Hsieh T. C. Lee AAML 57 69 0 18 Nov 2021
ε-weakened Robustness of Deep Neural Networks Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 48 18 0 29 Oct 2021
RoMA: a Method for Neural Network Robustness Measurement and Assessment Natan Levy Guy Katz OOD AAML 53 13 0 21 Oct 2021
A Universal Law of Robustness via Isoperimetry Sébastien Bubeck Mark Sellke 50 218 0 26 May 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 322 703 0 19 Oct 2020
Certifying Neural Network Robustness to Random Input Noise from Samples Brendon G. Anderson Somayeh Sojoudi AAML 22 9 0 15 Oct 2020
Probabilistic Safety for Bayesian Neural Networks Matthew Wicker Luca Laurenti A. Patané Marta Z. Kwiatkowska AAML 50 52 0 21 Apr 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 221 1,855 0 03 Mar 2020
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing Jinyuan Jia Xiaoyu Cao Binghui Wang Neil Zhenqiang Gong AAML 53 94 0 20 Dec 2019
Verification of Neural Network Control Policy Under Persistent Adversarial Perturbation Yuh-Shyang Wang Tsui-Wei Weng Luca Daniel AAML 50 16 0 18 Aug 2019
Quantitative Verification of Neural Networks And its Security Applications Teodora Baluta Shiqi Shen Shweta Shinde Kuldeep S. Meel P. Saxena AAML 61 105 0 25 Jun 2019
Machine Learning Testing: Survey, Landscapes and Horizons Jie M. Zhang Mark Harman Lei Ma Yang Liu VLM AILaw 80 752 0 19 Jun 2019
Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang Hongge Chen Chaowei Xiao Sven Gowal Robert Stanforth Yue Liu Duane S. Boning Cho-Jui Hsieh AAML 80 349 0 14 Jun 2019
$Provable robustness against all adversarial $l_p$-perturbations for $p\geq 1$$ Provable robustness against all adversarial $l_p$ -perturbations for $p\geq 1$ Francesco Croce Matthias Hein OOD 66 75 0 27 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 188 3,445 0 28 Mar 2019
On Evaluating Adversarial Robustness Nicholas Carlini Anish Athalye Nicolas Papernot Wieland Brendel Jonas Rauber Dimitris Tsipras Ian Goodfellow Aleksander Madry Alexey Kurakin ELM AAML 89 901 0 18 Feb 2019
Robustness of Neural Networks: A Probabilistic and Practical Approach Ravi Mangal A. Nori A. Orso AAML OOD 54 76 0 15 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 152 2,044 0 08 Feb 2019
Theoretical evidence for adversarial robustness through randomization Rafael Pinot Laurent Meunier Alexandre Araujo H. Kashima Florian Yger Cédric Gouy-Pailler Jamal Atif AAML 78 83 0 04 Feb 2019
A Statistical Approach to Assessing Neural Network Robustness Stefan Webb Tom Rainforth Yee Whye Teh M. P. Kumar AAML 60 83 0 17 Nov 2018
Analyzing Compositionality-Sensitivity of NLI Models Yixin Nie Yicheng Wang Joey Tianyi Zhou CoGe 57 82 0 16 Nov 2018
Semidefinite relaxations for certifying robustness to adversarial examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 100 439 0 02 Nov 2018
Efficient Neural Network Robustness Certification with General Activation Functions Huan Zhang Tsui-Wei Weng Pin-Yu Chen Cho-Jui Hsieh Luca Daniel AAML 93 763 0 02 Nov 2018
Robustness Guarantees for Bayesian Inference with Gaussian Processes L. Cardelli Marta Kwiatkowska Luca Laurenti A. Patané AAML 54 52 0 17 Sep 2018
Certified Adversarial Robustness with Additive Noise Bai Li Changyou Chen Wenlin Wang Lawrence Carin AAML 91 351 0 10 Sep 2018
Guiding Deep Learning System Testing using Surprise Adequacy Jinhan Kim R. Feldt S. Yoo AAML ELM 71 432 0 25 Aug 2018
Combinatorial Testing for Deep Learning Systems Lei Ma Fuyuan Zhang Minhui Xue Yue Liu Yang Liu Jianjun Zhao Yadong Wang AAML OffRL 50 73 0 20 Jun 2018
Towards Dependability Metrics for Neural Networks Chih-Hong Cheng Georg Nührenberg Chung-Hao Huang Harald Ruess Hirotoshi Yasuoka 39 44 0 06 Jun 2018
Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems Chih-Hong Cheng Chung-Hao Huang Hirotoshi Yasuoka 40 41 0 11 May 2018
Formal Security Analysis of Neural Networks using Symbolic Intervals Shiqi Wang Kexin Pei Justin Whitehouse Junfeng Yang Suman Jana AAML 84 478 0 28 Apr 2018
Towards Fast Computation of Certified Robustness for ReLU Networks Tsui-Wei Weng Huan Zhang Hongge Chen Zhao Song Cho-Jui Hsieh Duane S. Boning Inderjit S. Dhillon Luca Daniel AAML 108 695 0 25 Apr 2018
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems Lei Ma Felix Juefei Xu Fuyuan Zhang Jiyuan Sun Minhui Xue ... Ting Su Li Li Yang Liu Jianjun Zhao Yadong Wang ELM 67 622 0 20 Mar 2018
Stochastic Activation Pruning for Robust Adversarial Defense Guneet Singh Dhillon Kamyar Azizzadenesheli Zachary Chase Lipton Jeremy Bernstein Jean Kossaifi Aran Khanna Anima Anandkumar AAML 81 547 0 05 Mar 2018
Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression Nilaksh Das Madhuri Shanbhogue Shang-Tse Chen Fred Hohman Siwei Li Li-Wei Chen Michael E. Kounavis Duen Horng Chau FedML AAML 78 227 0 19 Feb 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 83 468 0 31 Jan 2018
Certified Defenses against Adversarial Examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 113 969 0 29 Jan 2018
Spatially Transformed Adversarial Examples Chaowei Xiao Jun-Yan Zhu Yue Liu Warren He M. Liu Basel Alomair AAML 76 524 0 08 Jan 2018
Deep Neural Networks as 0-1 Mixed Integer Linear Programs: A Feasibility Study M. Fischetti Jason Jo 47 81 0 17 Dec 2017
Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser Fangzhou Liao Ming Liang Yinpeng Dong Tianyu Pang Xiaolin Hu Jun Zhu 83 887 0 08 Dec 2017
Mitigating Adversarial Effects Through Randomization Cihang Xie Jianyu Wang Zhishuai Zhang Zhou Ren Alan Yuille AAML 113 1,061 0 06 Nov 2017
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 125 1,504 0 02 Nov 2017
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks D. Gopinath Guy Katz C. Păsăreanu Clark W. Barrett AAML 109 87 0 02 Oct 2017
Verifying Properties of Binarized Deep Neural Networks Nina Narodytska S. Kasiviswanathan L. Ryzhyk Shmuel Sagiv T. Walsh AAML 69 217 0 19 Sep 2017
Towards Proving the Adversarial Robustness of Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel J. Kochenderfer AAML OOD 80 118 0 08 Sep 2017