Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them

24 July 2021

Papers citing "Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them"

41 / 41 papers shown

Title
A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning Greg Gluch Shafi Goldwasser AAML 37 0 0 28 Apr 2025
Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics Taowen Wang Dongfang Liu James Liang Wenhao Yang Qifan Wang Cheng Han Jiebo Luo Ruixiang Tang Ruixiang Tang AAML 76 3 0 18 Nov 2024
Llama Guard 3 Vision: Safeguarding Human-AI Image Understanding Conversations Jianfeng Chi Ujjwal Karn Hongyuan Zhan Eric Michael Smith Javier Rando Yiming Zhang Kate Plawiak Zacharie Delpierre Coudert Kartikeya Upasani Mahesh Pasupuleti MLLM 3DH 49 20 0 15 Nov 2024
Low-Quality Image Detection by Hierarchical VAE Tomoyasu Nanaumi Kazuhiko Kawamoto Hiroshi Kera 27 0 0 20 Aug 2024
Towards Robust Vision Transformer via Masked Adaptive Ensemble Fudong Lin Jiadong Lou Xu Yuan Nianfeng Tzeng ViT AAML 28 1 0 22 Jul 2024
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers Jonas Ngnawé Sabyasachi Sahoo Y. Pequignot Frédéric Precioso Christian Gagné AAML 39 0 0 26 Jun 2024
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors Peter Lorenz Mario Fernandez Jens Müller Ullrich Kothe AAML 78 1 0 21 Jun 2024
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective Nils Philipp Walter Linara Adilova Jilles Vreeken Michael Kamp AAML 48 2 0 27 May 2024
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks Yunzhen Feng Tim G. J. Rudner Nikolaos Tsilivis Julia Kempe AAML BDL 43 1 0 27 Apr 2024
PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis Dipkamal Bhusal Md Tanvirul Alam M. K. Veerabhadran Michael Clifford Sara Rampazzi Nidhi Rastogi AAML 43 1 0 12 Apr 2024
SoK: Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge L. Fenaux Florian Kerschbaum AAML 39 0 0 22 Feb 2024
The Ultimate Combo: Boosting Adversarial Example Transferability by Composing Data Augmentations Zebin Yun Achi-Or Weingarten Eyal Ronen Mahmood Sharif 12 2 0 18 Dec 2023
Breaking Boundaries: Balancing Performance and Robustness in Deep Wireless Traffic Forecasting Romain Ilbert Thai V. Hoang Zonghua Zhang Themis Palpanas OOD AAML 31 0 0 16 Nov 2023
AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models Sicheng Zhu Ruiyi Zhang Bang An Gang Wu Joe Barrow Zichao Wang Furong Huang A. Nenkova Tong Sun SILM AAML 30 40 0 23 Oct 2023
$Is Certifying $\ell_p$ Robustness Still Worthwhile?$ Is Certifying $\ell_p$ Robustness Still Worthwhile? Ravi Mangal Klas Leino Zifan Wang Kai Hu Weicheng Yu Corina S. Pasareanu Anupam Datta Matt Fredrikson AAML OOD 27 1 0 13 Oct 2023
Splitting the Difference on Adversarial Training Matan Levi A. Kontorovich 37 4 0 03 Oct 2023
Beyond Labeling Oracles: What does it mean to steal ML models? Avital Shafran Ilia Shumailov Murat A. Erdogdu Nicolas Papernot AAML 24 4 0 03 Oct 2023
Baseline Defenses for Adversarial Attacks Against Aligned Language Models Neel Jain Avi Schwarzschild Yuxin Wen Gowthami Somepalli John Kirchenbauer Ping Yeh-Chiang Micah Goldblum Aniruddha Saha Jonas Geiping Tom Goldstein AAML 37 337 0 01 Sep 2023
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds Hejia Geng Peng Li AAML 34 3 0 20 Aug 2023
Robust Proxy: Improving Adversarial Robustness by Robust Proxy Learning Hong Joo Lee Yonghyun Ro AAML 28 3 0 27 Jun 2023
Visual Adversarial Examples Jailbreak Aligned Large Language Models Xiangyu Qi Kaixuan Huang Ashwinee Panda Peter Henderson Mengdi Wang Prateek Mittal AAML 25 137 0 22 Jun 2023
From Robustness to Explainability and Back Again Xuanxiang Huang João Marques-Silva 32 10 0 05 Jun 2023
Two Heads are Better than One: Towards Better Adversarial Robustness by Combining Transduction and Rejection Nils Palumbo Yang Guo Xi Wu Jiefeng Chen Yingyu Liang S. Jha AAML 23 0 0 27 May 2023
Stratified Adversarial Robustness with Rejection Jiefeng Chen Jayaram Raghuram Jihye Choi Xi Wu Yingyu Liang S. Jha 27 2 0 02 May 2023
Evaluation of Parameter-based Attacks against Embedded Neural Networks with Laser Injection Mathieu Dumont Kevin Hector Pierre-Alain Moëllic J. Dutertre S. Pontié AAML 23 2 0 25 Apr 2023
Simultaneous Adversarial Attacks On Multiple Face Recognition System Components Inderjeet Singh Kazuya Kakizaki Toshinori Araki CVBM AAML PICV 21 0 0 11 Apr 2023
Certifiable Black-Box Attacks with Randomized Adversarial Examples: Breaking Defenses with Provable Confidence Hanbin Hong Xinyu Zhang Binghui Wang Zhongjie Ba Yuan Hong AAML 22 2 0 10 Apr 2023
A Minimax Approach Against Multi-Armed Adversarial Attacks Detection Federica Granese Marco Romanelli S. Garg Pablo Piantanida AAML 19 0 0 04 Feb 2023
Publishing Efficient On-device Models Increases Adversarial Vulnerability Sanghyun Hong Nicholas Carlini Alexey Kurakin AAML 38 2 0 28 Dec 2022
Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes Sina Baharlouei Fatemeh Sheikholeslami Meisam Razaviyayn Zico Kolter AAML 19 6 0 26 Oct 2022
Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning Zhiyuan He Yijun Yang Pin-Yu Chen Qiang Xu Tsung-Yi Ho AAML 19 6 0 31 Aug 2022
Gradient Aligned Attacks via a Few Queries Xiangyuan Yang Jie Lin Hanlin Zhang Xinyu Yang Peng Zhao AAML 35 0 0 19 May 2022
A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks Jie Wang Minshuo Chen Tuo Zhao Wenjing Liao Yao Xie 17 7 0 04 May 2022
Detecting Adversaries, yet Faltering to Noise? Leveraging Conditional Variational AutoEncoders for Adversary Detection in the Presence of Noisy Images Dvij Kalaria Aritra Hazra P. Chakrabarti AAML 20 0 0 28 Nov 2021
Bugs in our Pockets: The Risks of Client-Side Scanning H. Abelson Ross J. Anderson S. Bellovin Josh Benaloh M. Blaze ... Ronald L. Rivest J. Schiller B. Schneier Vanessa J. Teague Carmela Troncoso 60 39 0 14 Oct 2021
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier Chong Xiang Saeed Mahloujifar Prateek Mittal VLM AAML 24 73 0 20 Aug 2021
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart Tianyu Pang Huishuai Zhang Di He Yinpeng Dong Hang Su Wei Chen Jun Zhu Tie-Yan Liu AAML 8 16 0 31 May 2021
Anomaly Detection of Adversarial Examples using Class-conditional Generative Adversarial Networks Hang Wang David J. Miller G. Kesidis GAN AAML 27 11 0 21 May 2021
BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability Luke Chang Katharina Dost Kaiqi Zhao Ambra Demontis Fabio Roli Gillian Dobbie Jörg Simon Wicker AAML 19 2 0 02 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 228 677 0 19 Oct 2020
A New Defense Against Adversarial Images: Turning a Weakness into a Strength Tao Yu Shengyuan Hu Chuan Guo Wei-Lun Chao Kilian Q. Weinberger AAML 52 101 0 16 Oct 2019