The Limitations of Deep Learning in Adversarial Settings

24 November 2015

Papers citing "The Limitations of Deep Learning in Adversarial Settings"

33 / 33 papers shown

Title
SuperPure: Efficient Purification of Localized and Distributed Adversarial Patches via Super-Resolution GAN Models Hossein Khalili Seongbin Park Venkat Bollapragada Nader Sehatbakhsh AAML 122 0 0 22 May 2025
Adversarial Attacks in Multimodal Systems: A Practitioner's Survey Shashank Kapoor Sanjay Surendranath Girija Lakshit Arora Dipen Pradhan Ankit Shetgaonkar Aman Raj AAML 87 0 0 06 May 2025
Fast Adversarial Training with Weak-to-Strong Spatial-Temporal Consistency in the Frequency Domain on Videos Songping Wang Hanqing Liu Yueming Lyu Xiantao Hu Ziwen He Wenjie Wang Caifeng Shan Lei Wang AAML 298 0 0 21 Apr 2025
From Visual Explanations to Counterfactual Explanations with Latent Diffusion Tung Luu Nam Le Duc Le Bac Le DiffM AAML FAtt 129 0 0 12 Apr 2025
On the Promise for Assurance of Differentiable Neurosymbolic Reasoning Paradigms Luke E. Richards Jessie Yaros Jasen Babcock Coung Ly Robin Cosbey Timothy Doster Cynthia Matuszek NAI 88 0 0 13 Feb 2025
CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers Matan Ben-Tov Daniel Deutch Nave Frost Mahmood Sharif AAML 152 0 0 20 Jan 2025
On the uncertainty principle of neural networks Jun-Jie Zhang Dong-xiao Zhang Jian-Nan Chen L. Pang Deyu Meng 79 2 0 17 Jan 2025
Aligning Generalisation Between Humans and Machines Filip Ilievski Barbara Hammer F. V. Harmelen Benjamin Paassen S. Saralajew ... Vered Shwartz Gabriella Skitalinskaya Clemens Stachl Gido M. van de Ven T. Villmann 195 1 0 23 Nov 2024
Prompt-Driven Contrastive Learning for Transferable Adversarial Attacks Hunmin Yang Jongoh Jeong Kuk-Jin Yoon AAML VLM 81 5 0 30 Jul 2024
One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models Hao Fang Jiawei Kong Wenbo Yu Bin Chen Jiawei Li Hao Wu Ke Xu Ke Xu AAML VLM 75 13 0 08 Jun 2024
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective Nils Philipp Walter Linara Adilova Jilles Vreeken Michael Kamp AAML 71 2 0 27 May 2024
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples Antonio Emanuele Cinà Jérôme Rony Maura Pintor Christian Scano Ambra Demontis Battista Biggio Ismail Ben Ayed Fabio Roli ELM AAML SILM 75 9 0 30 Apr 2024
Towards Adversarially Robust Dataset Distillation by Curvature Regularization Eric Xue Yijiang Li Haoyang Liu Yifan Shen Haohan Wang Haohan Wang DD 87 8 0 15 Mar 2024
Machine unlearning through fine-grained model parameters perturbation Zhiwei Zuo Zhuo Tang KenLi Li Anwitaman Datta AAML MU 43 0 0 09 Jan 2024
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 53 0 0 18 Oct 2023
SAIF: Sparse Adversarial and Imperceptible Attack Framework Tooba Imtiaz Morgan Kohler Jared Miller Zifeng Wang Octavia Camps Mario Sznaier Octavia Camps Jennifer Dy AAML 55 0 0 14 Dec 2022
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks Yonggan Fu Qixuan Yu Yang Zhang Shan-Hung Wu Ouyang Xu David D. Cox Yingyan Lin AAML OOD 59 30 0 26 Oct 2021
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 62 37 0 24 Sep 2021
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency Yonggan Fu Yang Zhao Qixuan Yu Chaojian Li Yingyan Lin AAML 66 14 0 11 Sep 2021
Adversarial Filters for Secure Modulation Classification A. Berian K. Staab N. Teku G. Ditzler T. Bose Ravi Tandon AAML 37 7 0 15 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 64 73 0 07 Aug 2020
ConAML: Constrained Adversarial Machine Learning for Cyber-Physical Systems Jiangnan Li Yingyuan Yang Jinyuan Stella Sun K. Tomsovic Jin Young Lee AAML 68 53 0 12 Mar 2020
Algorithmic decision-making in AVs: Understanding ethical and technical concerns for smart cities H. S. M. Lim Araz Taeihagh 41 83 0 29 Oct 2019
MaskedNet: The First Hardware Inference Engine Aiming Power Side-Channel Protection Anuj Dubey Rosario Cammarota Aydin Aysu AAML 40 78 0 29 Oct 2019
Poisoning Behavioral Malware Clustering Battista Biggio Konrad Rieck Andrea Valenza Christian Wressnegger Igino Corona Giorgio Giacinto Fabio Roli 25 152 0 25 Nov 2018
Generating Natural Adversarial Examples Zhengli Zhao Dheeru Dua Sameer Singh GAN AAML 135 599 0 31 Oct 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 98 2,140 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 79 217 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 68 63 0 19 May 2017
Simple Black-Box Adversarial Perturbations for Deep Networks Nina Narodytska S. Kasiviswanathan AAML 50 237 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 47 3,660 0 08 Feb 2016
How transferable are features in deep neural networks? J. Yosinski Jeff Clune Yoshua Bengio Hod Lipson OOD 143 8,309 0 06 Nov 2014
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 86 1,580 0 27 Jun 2012