Certified Defenses against Adversarial Examples

29 January 2018

Papers citing "Certified Defenses against Adversarial Examples"

50 / 250 papers shown

Title
Practical Convex Formulation of Robust One-hidden-layer Neural Network Training Yatong Bai Tanmay Gautam Yujie Gai Somayeh Sojoudi AAML 27 3 0 25 May 2021
A Review of Formal Methods applied to Machine Learning Caterina Urban Antoine Miné 39 55 0 06 Apr 2021
Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting Adversarial Patches Nan Ji YanFei Feng Haidong Xie Xueshuang Xiang Naijin Liu AAML 58 33 0 16 Mar 2021
Adversarial Training is Not Ready for Robot Learning Mathias Lechner Ramin Hasani Radu Grosu Daniela Rus T. Henzinger AAML 38 34 0 15 Mar 2021
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness Jacob D. Abernethy Pranjal Awasthi Satyen Kale AAML 27 6 0 01 Mar 2021
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS Felix O. Olowononi D. Rawat Chunmei Liu 36 133 0 14 Feb 2021
On the Paradox of Certified Training Nikola Jovanović Mislav Balunović Maximilian Baader Martin Vechev OOD 28 13 0 12 Feb 2021
Fast Training of Provably Robust Neural Networks by SingleProp Akhilan Boopathy Tsui-Wei Weng Sijia Liu Pin-Yu Chen Gaoyuan Zhang Luca Daniel AAML 11 7 0 01 Feb 2021
A Comprehensive Evaluation Framework for Deep Model Robustness Jun Guo Wei Bao Jiakai Wang Yuqing Ma Xing Gao Gang Xiao Aishan Liu Zehao Zhao Xianglong Liu Wenjun Wu AAML ELM 38 55 0 24 Jan 2021
Fundamental Tradeoffs in Distributionally Adversarial Training M. Mehrabi Adel Javanmard Ryan A. Rossi Anup B. Rao Tung Mai AAML 20 18 0 15 Jan 2021
A Study on the Uncertainty of Convolutional Layers in Deep Neural Networks Hao Shen Sihong Chen Ran Wang 30 5 0 27 Nov 2020
Certified Monotonic Neural Networks Xingchao Liu Xing Han Na Zhang Qiang Liu 24 79 0 20 Nov 2020
Adversarially Robust Classification based on GLRT Bhagyashree Puranik Upamanyu Madhow Ramtin Pedarsani VLM AAML 23 4 0 16 Nov 2020
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations Jinyuan Jia Binghui Wang Xiaoyu Cao Hongbin Liu Neil Zhenqiang Gong 16 24 0 15 Nov 2020
Adversarial Robust Training of Deep Learning MRI Reconstruction Models Francesco Calivá Kaiyang Cheng Rutwik Shah V. Pedoia OOD AAML MedIm 30 10 0 30 Oct 2020
Precise Statistical Analysis of Classification Accuracies for Adversarial Training Adel Javanmard Mahdi Soltanolkotabi AAML 33 62 0 21 Oct 2020
Evaluating the Safety of Deep Reinforcement Learning Models using Semi-Formal Verification Davide Corsi Enrico Marchesini Alessandro Farinelli OffRL 14 2 0 19 Oct 2020
Viewmaker Networks: Learning Views for Unsupervised Representation Learning Alex Tamkin Mike Wu Noah D. Goodman SSL 28 64 0 14 Oct 2020
Adversarial Boot Camp: label free certified robustness in one epoch Ryan Campbell Chris Finlay Adam M. Oberman AAML 25 0 0 05 Oct 2020
Block-wise Image Transformation with Secret Key for Adversarially Robust Defense Maungmaung Aprilpyone Hitoshi Kiya 29 57 0 02 Oct 2020
Utility is in the Eye of the User: A Critique of NLP Leaderboards Kawin Ethayarajh Dan Jurafsky ELM 24 51 0 29 Sep 2020
Deep Learning & Software Engineering: State of Research and Future Directions P. Devanbu Matthew B. Dwyer Sebastian G. Elbaum M. Lowry Kevin Moran Denys Poshyvanyk Baishakhi Ray Rishabh Singh Xiangyu Zhang 11 22 0 17 Sep 2020
Defending Against Multiple and Unforeseen Adversarial Videos Shao-Yuan Lo Vishal M. Patel AAML 31 23 0 11 Sep 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo-wen Li AAML 33 128 0 09 Sep 2020
Rethinking Non-idealities in Memristive Crossbars for Adversarial Robustness in Neural Networks Abhiroop Bhattacharjee Priyadarshini Panda AAML 28 19 0 25 Aug 2020
Robust Deep Reinforcement Learning through Adversarial Loss Tuomas P. Oikarinen Wang Zhang Alexandre Megretski Luca Daniel Tsui-Wei Weng AAML 44 94 0 05 Aug 2020
Robust Machine Learning via Privacy/Rate-Distortion Theory Ye Wang Shuchin Aeron Adnan Siraj Rakin T. Koike-Akino P. Moulin OOD 22 6 0 22 Jul 2020
AdvFoolGen: Creating Persistent Troubles for Deep Classifiers Yuzhen Ding Nupur Thakur Baoxin Li AAML 24 3 0 20 Jul 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor A. Madry 37 417 0 16 Jul 2020
Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations Chaoning Zhang Philipp Benz Tooba Imtiaz In-So Kweon SSL AAML 22 117 0 13 Jul 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification Rohan Taori Achal Dave Vaishaal Shankar Nicholas Carlini Benjamin Recht Ludwig Schmidt OOD 33 536 0 01 Jul 2020
Counterexample-Guided Learning of Monotonic Neural Networks Aishwarya Sivaraman G. Farnadi T. Millstein Mathias Niepert 24 50 0 16 Jun 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 24 81 0 15 Jun 2020
Defensive Approximation: Securing CNNs using Approximate Computing Amira Guesmi Ihsen Alouani Khaled N. Khasawneh M. Baklouti T. Frikha Mohamed Abid Nael B. Abu-Ghazaleh AAML 19 37 0 13 Jun 2020
D-square-B: Deep Distribution Bound for Natural-looking Adversarial Attack Qiuling Xu Guanhong Tao Xiangyu Zhang AAML 22 2 0 12 Jun 2020
Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao Clayton Scott Masashi Sugiyama 29 45 0 28 May 2020
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking Chong Xiang A. Bhagoji Vikash Sehwag Prateek Mittal AAML 30 29 0 17 May 2020
Encryption Inspired Adversarial Defense for Visual Classification Maungmaung Aprilpyone Hitoshi Kiya 18 32 0 16 May 2020
Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition Tianhang Zheng Sheng Liu Changyou Chen Junsong Yuan Baochun Li K. Ren AAML 21 17 0 14 May 2020
Blind Backdoors in Deep Learning Models Eugene Bagdasaryan Vitaly Shmatikov AAML FedML SILM 46 298 0 08 May 2020
Robustness Certification of Generative Models M. Mirman Timon Gehr Martin Vechev AAML 43 22 0 30 Apr 2020
Provably robust deep generative models Filipe Condessa Zico Kolter AAML OOD 6 5 0 22 Apr 2020
Certifying Joint Adversarial Robustness for Model Ensembles M. Jonas David Evans AAML 21 2 0 21 Apr 2020
Single-step Adversarial training with Dropout Scheduling S. VivekB. R. Venkatesh Babu OOD AAML 18 71 0 18 Apr 2020
When the Guard failed the Droid: A case study of Android malware Harel Berger Chen Hajaj A. Dvir AAML 30 7 0 31 Mar 2020
Safety-Aware Hardening of 3D Object Detection Neural Network Systems Chih-Hong Cheng 3DPC 24 12 0 25 Mar 2020
Diversity can be Transferred: Output Diversification for White- and Black-box Attacks Y. Tashiro Yang Song Stefano Ermon AAML 14 13 0 15 Mar 2020
When are Non-Parametric Methods Robust? Robi Bhattacharjee Kamalika Chaudhuri AAML 42 28 0 13 Mar 2020
Model Assertions for Monitoring and Improving ML Models Daniel Kang Deepti Raghavan Peter Bailis Matei A. Zaharia 8 58 0 03 Mar 2020
Analyzing Accuracy Loss in Randomized Smoothing Defenses Yue Gao Harrison Rosenberg Kassem Fawaz S. Jha Justin Hsu AAML 24 6 0 03 Mar 2020