Adversarial Example

Adversarial examples are subtly altered inputs designed to fool machine learning models, primarily deep neural networks (DNNs), into making incorrect predictions. Current research focuses on improving model robustness against these attacks, exploring techniques like ensemble methods, multi-objective representation learning, and adversarial training, often applied to architectures such as ResNets and Vision Transformers. Understanding and mitigating the threat of adversarial examples is crucial for ensuring the reliability and security of AI systems across diverse applications, from image classification and natural language processing to malware detection and autonomous driving. The development of robust defenses and effective attack detection methods remains a significant area of ongoing investigation.

Papers

December 13, 2023

Accelerating the Global Aggregation of Local Explanations
Alon Mor, Yonatan Belinkov, Benny Kimelfeld
Adversarial Example Local Explanation Anchor Graph Global Aggregation

December 12, 2023

December 9, 2023

Poisoning $\times$ Evasion: Symbiotic Adversarial Robustness for Graph Neural Networks
Ege Erdogan, Simon Geisler, Stephan Günnemann
Graph Neural Network Adversarial Attack Adversarial Example Adversarial Robustness Threat Model

December 8, 2023

December 7, 2023

OT-Attack: Enhancing Adversarial Transferability of Vision-Language Models via Optimal Transport Optimization
Dongchen Han, Xiaojun Jia, Yang Bai, Jindong Gu, Yang Liu, Xiaochun Cao
Adversarial Attack Vision Language Model Adversarial Example Optimal Transport

December 6, 2023

Class Incremental Learning for Adversarial Robustness
Seungju Cho, Hongsin Lee, Changick Kim
Adversarial Example Adversarial Training Adversarial Robustness Incremental Learning Class Incremental Learning

December 5, 2023

Generating Visually Realistic Adversarial Patch
Xiaosen Wang, Kunyu Wang
Adversarial Example Adversarial Patch

December 4, 2023

December 3, 2023

TranSegPGD: Improving Transferability of Adversarial Examples on Semantic Segmentation
Xiaojun Jia, Jindong Gu, Yihao Huang, Simeng Qin, Qing Guo, Yang Liu, Xiaochun Cao
Adversarial Attack Semantic Segmentation Adversarial Example Task Transferability Adversarial Text

November 30, 2023

Universal Backdoor Attacks
Benjamin Schneider, Nils Lukas, Florian Kerschbaum
Adversarial Example Backdoor Attack Poisoning Attack Transferable Attack Universal Backdoor

November 28, 2023

November 27, 2023

Adversarial Doodles: Interpretable and Human-drawable Attacks Provide Describable Insights
Ryoya Nara, Yusuke Matsui
Adversarial Attack Adversarial Example DCU Insight AQ Imperceptible Attack Adversarial Challenge