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Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks

14 November 2015

Papers citing "Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks"

40 / 40 papers shown

Title
A Structured Tour of Optimization with Finite Differences Marco Rando C. Molinari Lorenzo Rosasco S. Villa 155 0 0 26 May 2025
Human Aligned Compression for Robust Models Samuel Räber Andreas Plesner Till Aczél Roger Wattenhofer AAML 99 0 0 16 Apr 2025
DV-FSR: A Dual-View Target Attack Framework for Federated Sequential Recommendation Qitao Qin Yucong Luo Mingyue Cheng Qingyang Mao Chenyi Lei FedML 104 0 0 31 Dec 2024
Fall Leaf Adversarial Attack on Traffic Sign Classification Anthony Etim Jakub Szefer AAML 127 3 0 27 Nov 2024
Adversarial Prompt Distillation for Vision-Language Models Lin Luo Xin Wang Bojia Zi Shihao Zhao Xingjun Ma Yu-Gang Jiang AAML VLM 135 4 0 22 Nov 2024
Bridging Today and the Future of Humanity: AI Safety in 2024 and Beyond Shanshan Han 145 1 0 09 Oct 2024
On Using Certified Training towards Empirical Robustness Alessandro De Palma Serge Durand Zakaria Chihani François Terrier Caterina Urban OOD AAML 74 1 0 02 Oct 2024
On the Robustness of Kolmogorov-Arnold Networks: An Adversarial Perspective Tal Alter Raz Lapid Moshe Sipper AAML 90 6 0 25 Aug 2024
Distilling Aggregated Knowledge for Weakly-Supervised Video Anomaly Detection Jash Dalvi Ali Dabouei Gunjan Dhanuka Min Xu 57 0 0 05 Jun 2024
Towards Adversarially Robust Dataset Distillation by Curvature Regularization Eric Xue Yijiang Li Haoyang Liu Yifan Shen Haohan Wang Haohan Wang DD 115 8 0 15 Mar 2024
Accelerated Smoothing: A Scalable Approach to Randomized Smoothing Devansh Bhardwaj Kshitiz Kaushik Sarthak Gupta AAML 82 0 0 12 Feb 2024
Set-Based Training for Neural Network Verification Lukas Koller Tobias Ladner Matthias Althoff AAML 82 2 0 26 Jan 2024
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems Guangjing Wang Ce Zhou Yuanda Wang Bocheng Chen Hanqing Guo Qiben Yan AAML SILM 111 3 0 20 Nov 2023
Tailoring Adversarial Attacks on Deep Neural Networks for Targeted Class Manipulation Using DeepFool Algorithm S. M. Fazle J. Mondal Meem Arafat Manab Xi Xiao Sarfaraz Newaz AAML 77 0 0 18 Oct 2023
Generating Less Certain Adversarial Examples Improves Robust Generalization Minxing Zhang Michael Backes Xiao Zhang AAML 107 1 0 06 Oct 2023
Decentralized Adversarial Training over Graphs Ying Cao Elsa Rizk Stefan Vlaski Ali H. Sayed AAML 114 1 0 23 Mar 2023
Nash Equilibria, Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization Soroosh Shafieezadeh-Abadeh Liviu Aolaritei Florian Dorfler Daniel Kuhn 123 21 0 07 Mar 2023
Mitigating Adversarial Effects of False Data Injection Attacks in Power Grid Farhin Farhad Riya Shahinul Hoque Jinyuan Stella Sun Jiangnan Li Hairong Qi Hairong Qi AAML AI4CE 66 0 0 29 Jan 2023
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 107 38 0 24 Sep 2021
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation Karan Goel Albert Gu Yixuan Li Christopher Ré 84 121 0 15 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 94 73 0 07 Aug 2020
Architecture Selection via the Trade-off Between Accuracy and Robustness Zhun Deng Cynthia Dwork Jialiang Wang Yao-Min Zhao AAML 94 3 0 04 Jun 2019
Poisoning Behavioral Malware Clustering Battista Biggio Konrad Rieck Andrea Valenza Christian Wressnegger Igino Corona Giorgio Giacinto Fabio Roli 65 152 0 25 Nov 2018
Security Evaluation of Pattern Classifiers under Attack Battista Biggio Giorgio Fumera Fabio Roli AAML 65 444 0 02 Sep 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 157 2,153 0 21 Aug 2017
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction Bin Liang Hongcheng Li Miaoqiang Su Xirong Li Wenchang Shi Xiaofeng Wang AAML 86 217 0 23 May 2017
MTDeep: Boosting the Security of Deep Neural Nets Against Adversarial Attacks with Moving Target Defense Sailik Sengupta Tathagata Chakraborti S. Kambhampati AAML 97 63 0 19 May 2017
Adversarial Examples Detection in Deep Networks with Convolutional Filter Statistics Xin Li Fuxin Li GAN AAML 110 365 0 22 Dec 2016
Simple Black-Box Adversarial Perturbations for Deep Networks Nina Narodytska S. Kasiviswanathan AAML 67 239 0 19 Dec 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 75 3,678 0 08 Feb 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 110 3,962 0 24 Nov 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 362 19,660 0 09 Mar 2015
Analysis of classifiers' robustness to adversarial perturbations Alhussein Fawzi Omar Fawzi P. Frossard AAML 95 361 0 09 Feb 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014
Towards Deep Neural Network Architectures Robust to Adversarial Examples S. Gu Luca Rigazio AAML 76 843 0 11 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 169 3,271 0 05 Dec 2014
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks P. Sermanet David Eigen Xiang Zhang Michaël Mathieu Rob Fergus Yann LeCun ObjD 151 5,006 0 21 Dec 2013
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 275 14,927 1 21 Dec 2013
Do Deep Nets Really Need to be Deep? Lei Jimmy Ba R. Caruana 163 2,117 0 21 Dec 2013
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 112 1,590 0 27 Jun 2012