Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods

20 May 2017

Papers citing "Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods"

50 / 336 papers shown

Title
Adversarial Attacks in Multimodal Systems: A Practitioner's Survey Shashank Kapoor Sanjay Surendranath Girija Lakshit Arora Dipen Pradhan Ankit Shetgaonkar Aman Raj AAML 77 0 0 06 May 2025
What's Pulling the Strings? Evaluating Integrity and Attribution in AI Training and Inference through Concept Shift Jiamin Chang Yiming Li Hammond Pearce Ruoxi Sun Bo-wen Li Minhui Xue 38 0 0 28 Apr 2025
Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models Patrick Müller Alexander Braun M. Keuper 59 0 0 25 Apr 2025
Poisoned Source Code Detection in Code Models Ehab Ghannoum Mohammad Ghafari AAML 65 0 0 19 Feb 2025
Unified Face Matching and Physical-Digital Spoofing Attack Detection Arun Kunwar Ajita Rattani CVBM AAML 49 0 0 17 Jan 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 79 3 0 18 Nov 2024
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training Tejaswini Medi Steffen Jung M. Keuper AAML 44 3 0 30 Oct 2024
An Adversarial Perspective on Machine Unlearning for AI Safety Jakub Łucki Boyi Wei Yangsibo Huang Peter Henderson F. Tramèr Javier Rando MU AAML 73 32 0 26 Sep 2024
Cartan moving frames and the data manifolds Eliot Tron Rita Fioresi Nicolas Couellan Stéphane Puechmorel 51 1 0 18 Sep 2024
A3Rank: Augmentation Alignment Analysis for Prioritizing Overconfident Failing Samples for Deep Learning Models Zhengyuan Wei Haipeng Wang Qili Zhou William Chan 34 0 0 19 Jul 2024
SPLITZ: Certifiable Robustness via Split Lipschitz Randomized Smoothing Meiyu Zhong Ravi Tandon 44 3 0 03 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 42 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
Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI Robert Honig Javier Rando Nicholas Carlini Florian Tramèr WIGM AAML 55 16 0 17 Jun 2024
HOLMES: to Detect Adversarial Examples with Multiple Detectors Jing Wen AAML 41 0 0 30 May 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
Trustworthy Actionable Perturbations Jesse Friedbaum Sudarshan Adiga Ravi Tandon AAML 38 2 0 18 May 2024
From Attack to Defense: Insights into Deep Learning Security Measures in Black-Box Settings Firuz Juraev Mohammed Abuhamad Eric Chan-Tin George K. Thiruvathukal Tamer Abuhmed AAML 41 0 0 03 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
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning F. Mumuni A. Mumuni AAML 37 5 0 11 Mar 2024
AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement Learning Vasudev Gohil Satwik Patnaik D. Kalathil Jeyavijayan Rajendran AAML 40 3 0 21 Feb 2024
Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment Xabier Echeberria-Barrio Amaia Gil-Lerchundi Jon Egana-Zubia Raul Orduna Urrutia AAML 32 6 0 12 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 31 16 0 02 Feb 2024
FIMBA: Evaluating the Robustness of AI in Genomics via Feature Importance Adversarial Attacks Heorhii Skovorodnikov Hoda AlKhzaimi AAML 30 2 0 19 Jan 2024
Explaining high-dimensional text classifiers Odelia Melamed Rich Caruana 23 0 0 22 Nov 2023
Toward Stronger Textual Attack Detectors Pierre Colombo Marine Picot Nathan Noiry Guillaume Staerman Pablo Piantanida 57 5 0 21 Oct 2023
Adversarial Attacks Against Uncertainty Quantification Emanuele Ledda Daniele Angioni Giorgio Piras Giorgio Fumera Battista Biggio Fabio Roli AAML 32 2 0 19 Sep 2023
Certifying LLM Safety against Adversarial Prompting Aounon Kumar Chirag Agarwal Suraj Srinivas Aaron Jiaxun Li S. Feizi Himabindu Lakkaraju AAML 27 165 0 06 Sep 2023
Everyone Can Attack: Repurpose Lossy Compression as a Natural Backdoor Attack Sze Jue Yang Q. Nguyen Chee Seng Chan Khoa D. Doan AAML DiffM 32 0 0 31 Aug 2023
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds Hejia Geng Peng Li AAML 34 3 0 20 Aug 2023
A LLM Assisted Exploitation of AI-Guardian Nicholas Carlini ELM SILM 24 15 0 20 Jul 2023
Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation Asif Hanif Muzammal Naseer Salman Khan M. Shah Fahad Shahbaz Khan AAML OOD 38 3 0 14 Jul 2023
Adversarial Evasion Attacks Practicality in Networks: Testing the Impact of Dynamic Learning Mohamed el Shehaby Ashraf Matrawy AAML 33 7 0 08 Jun 2023
Exploiting Frequency Spectrum of Adversarial Images for General Robustness Chun Yang Tan K. Kawamoto Hiroshi Kera AAML OOD 34 1 0 15 May 2023
Adversarial Examples Detection with Enhanced Image Difference Features based on Local Histogram Equalization Z. Yin Shaowei Zhu Han Su Jianteng Peng Wanli Lyu Bin Luo AAML 31 2 0 08 May 2023
Provable Robustness for Streaming Models with a Sliding Window Aounon Kumar Vinu Sankar Sadasivan S. Feizi OOD AAML AI4TS 19 1 0 28 Mar 2023
Boosting Verified Training for Robust Image Classifications via Abstraction Zhaodi Zhang Zhiyi Xue Yang Chen Si Liu Yueling Zhang Jiaheng Liu Min Zhang 33 4 0 21 Mar 2023
Immune Defense: A Novel Adversarial Defense Mechanism for Preventing the Generation of Adversarial Examples Jinwei Wang Hao Wu Haihua Wang Jiawei Zhang X. Luo Bin Ma AAML 25 0 0 08 Mar 2023
Randomness in ML Defenses Helps Persistent Attackers and Hinders Evaluators Keane Lucas Matthew Jagielski Florian Tramèr Lujo Bauer Nicholas Carlini AAML 30 9 0 27 Feb 2023
PAD: Towards Principled Adversarial Malware Detection Against Evasion Attacks Deqiang Li Shicheng Cui Yun Li Jia Xu Fu Xiao Shouhuai Xu AAML 54 18 0 22 Feb 2023
Are Defenses for Graph Neural Networks Robust? Felix Mujkanovic Simon Geisler Stephan Günnemann Aleksandar Bojchevski OOD AAML 21 56 0 31 Jan 2023
Inference Time Evidences of Adversarial Attacks for Forensic on Transformers Hugo Lemarchant Liang Li Yiming Qian Yuta Nakashima Hajime Nagahara ViT AAML 43 0 0 31 Jan 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing Yatong Bai Brendon G. Anderson Aerin Kim Somayeh Sojoudi AAML 36 18 0 29 Jan 2023
SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning Maxwell Standen Junae Kim Claudia Szabo AAML 32 5 0 11 Jan 2023
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks Yan Scholten Jan Schuchardt Simon Geisler Aleksandar Bojchevski Stephan Günnemann AAML 26 15 0 05 Jan 2023
Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene Understanding Mengya Xu Mobarakol Islam Ben Glocker Hongliang Ren 31 1 0 22 Dec 2022
Targeted Adversarial Attacks against Neural Network Trajectory Predictors Kai Liang Tan Jun Wang Y. Kantaros AAML 33 14 0 08 Dec 2022
Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning Hongbin Liu Wenjie Qu Jinyuan Jia Neil Zhenqiang Gong SSL 28 6 0 06 Dec 2022
Adversarial Artifact Detection in EEG-Based Brain-Computer Interfaces Xiaoqing Chen Dongrui Wu AAML 30 2 0 28 Nov 2022
Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning Ethan Rathbun Kaleel Mahmood Sohaib Ahmad Caiwen Ding Marten van Dijk AAML 19 4 0 26 Nov 2022