Adversarial Attack Detection

Adversarial attack detection focuses on identifying subtly manipulated inputs—designed to fool machine learning models—in various applications, from medical imaging to autonomous systems. Current research emphasizes developing robust, attack-agnostic detection methods using diverse architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs like LSTMs), and autoencoders, often incorporating techniques like self-supervised learning, feature attribution analysis, and distributional distance comparisons. Successful detection is crucial for ensuring the reliability and security of AI systems across numerous domains, mitigating risks associated with misclassifications or compromised functionality. The development of effective and efficient detection methods is a significant area of ongoing research, with a focus on improving accuracy and reducing reliance on large labeled datasets.

Papers

November 7, 2024

Neural Fingerprints for Adversarial Attack Detection
Haim Fisher, Moni Shahar, Yehezkel S. Resheff
Deep Learning Model Adversarial Example Image Classification Supervised ImageNet Adversarial Attack Detection

August 16, 2024

DFT-Based Adversarial Attack Detection in MRI Brain Imaging: Enhancing Diagnostic Accuracy in Alzheimer's Case Studies
Mohammad Hossein Najafi, Mohammad Morsali, Mohammadmahdi Vahediahmar, Saeed Bagheri Shouraki
Adversarial Attack Case Study Medical Image Alzheimer'S Disease Adversarial Behavior Diagnostic Accuracy Adversarial Attack Detection

July 5, 2024

Self-Supervised Representation Learning for Adversarial Attack Detection
Yi Li, Plamen Angelov, Neeraj Suri
Self Supervised Self Supervised Representation Learning Adversarial Detection Adversarial Attack Detection

April 12, 2024

PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis
Dipkamal Bhusal, Md Tanvirul Alam, Monish K. Veerabhadran, Michael Clifford, Sara Rampazzi, Nidhi Rastogi
Adversarial Attack Human Prediction Adversarial Sample Feature Attribution Adversarial Detection Adversarial Attack Detection Predicate Argument Structure

November 10, 2023

Robust Adversarial Attacks Detection for Deep Learning based Relative Pose Estimation for Space Rendezvous
Ziwei Wang, Nabil Aouf, Jose Pizarro, Christophe Honvault
Deep Learning Adversarial Attack Relative Pose Adversarial Detection Rendezvous Problem Autonomous Spacecraft Adversarial Attack Detection Relative Positional

June 27, 2023

On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection
Songyang Gao, Shihan Dou, Qi Zhang, Xuanjing Huang, Jin Ma, Ying Shan
Adversarial Sample Adversarial Detection Adversarial Attack Detection

May 31, 2023

Graph-based methods coupled with specific distributional distances for adversarial attack detection
Dwight Nwaigwe, Lucrezia Carboni, Martial Mermillod, Sophie Achard, Michel Dojat
Neural Network Adversarial Attack Sparse Graph Layer Wise Relevance Propagation Graph Analysis Adversarial Attack Detection Graph Based Method Distance Distribution

February 4, 2023

A Minimax Approach Against Multi-Armed Adversarial Attacks Detection
Federica Granese, Marco Romanelli, Siddharth Garg, Pablo Piantanida
Adversarial Example Minimax Optimization Pre Training Data Detection Adversarial Attack Detection

December 20, 2022

Multi-head Uncertainty Inference for Adversarial Attack Detection
Yuqi Yang, Songyun Yang, Jiyang Xie. Zhongwei Si, Kai Guo, Ke Zhang, Kongming Liang
Adversarial Attack Adversarial Example Adversarial DEfense Adversarial Attack Detection

June 1, 2022

Attack-Agnostic Adversarial Detection
Jiaxin Cheng, Mohamed Hussein, Jay Billa, Wael AbdAlmageed
Adversarial Attack Adversarial Example Adversarial Perturbation Adversarial Detection Adversarial Attack Detection

May 9, 2022

Btech thesis report on adversarial attack detection and purification of adverserially attacked images
Dvij Kalaria
Adversarial Attack Native Robustness Deep Learning Model Machine Learning Model Digital Image Electronic Thesis Adversarial Attack Detection

Adversarial Attack Detection

Papers

Neural Fingerprints for Adversarial Attack Detection

DFT-Based Adversarial Attack Detection in MRI Brain Imaging: Enhancing Diagnostic Accuracy in Alzheimer's Case Studies

Self-Supervised Representation Learning for Adversarial Attack Detection

PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis

Robust Adversarial Attacks Detection for Deep Learning based Relative Pose Estimation for Space Rendezvous

On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection

Graph-based methods coupled with specific distributional distances for adversarial attack detection

A Minimax Approach Against Multi-Armed Adversarial Attacks Detection

Multi-head Uncertainty Inference for Adversarial Attack Detection

Attack-Agnostic Adversarial Detection

Btech thesis report on adversarial attack detection and purification of adverserially attacked images