Adversarial Attack

Adversarial attacks aim to deceive machine learning models by subtly altering input data, causing misclassifications or other erroneous outputs. Current research focuses on developing more robust models and detection methods, exploring various attack strategies across different model architectures (including vision transformers, recurrent neural networks, and graph neural networks) and data types (images, text, signals, and tabular data). Understanding and mitigating these attacks is crucial for ensuring the reliability and security of AI systems in diverse applications, from autonomous vehicles to medical diagnosis and cybersecurity.

1813papers

Papers - Page 70

May 29, 2023

UMD: Unsupervised Model Detection for X2X Backdoor Attacks
Zhen Xiang, Zidi Xiong, Bo Li
Masked Diffusion Adversarial Attack Unsupervised Detection
Exploiting Explainability to Design Adversarial Attacks and Evaluate Attack Resilience in Hate-Speech Detection Models
Pranath Reddy Kumbam, Sohaib Uddin Syed, Prashanth Thamminedi, Suhas Harish, Ian Perera, Bonnie J. Dorr
Hate Speech Detection Adversarial Attack Hate Speech Detection Model High Explainability
From Adversarial Arms Race to Model-centric Evaluation: Motivating a Unified Automatic Robustness Evaluation Framework
Yangyi Chen, Hongcheng Gao, Ganqu Cui, Lifan Yuan, Dehan Kong, Hanlu Wu, Ning Shi, Bo Yuan, Longtao Huang, Hui Xue, Zhiyuan Liu, Maosong Sun+1
Robustness Evaluation Framework Robustness Evaluation Adversarial Attack Model Centric Evaluation
Fourier Analysis on Robustness of Graph Convolutional Neural Networks for Skeleton-based Action Recognition
Nariki Tanaka, Hiroshi Kera, Kazuhiko Kawamoto
Fourier Analysis Native Robustness Skeleton Based Action Recognition Adversarial Training Graph Convolutional Neural Network Adversarial Attack Graph Fourier
Membership Inference Attacks against Language Models via Neighbourhood Comparison
Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schölkopf, Mrinmaya Sachan, Taylor Berg-Kirkpatrick
Membership Inference Attack Language Model Based Attack Adversarial Attack Training Data Neighborhood Level

May 27, 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, Somesh Jha
Transductive Approach Human Head Adversarial Attack Transmission Data Better Adversarial Robustness Risky Prompt Rejection Adversarial Perturbation
Adversarial Attack On Yolov5 For Traffic And Road Sign Detection
Sanyam Jain
Sign Detection Adversarial Attack Object Detection Algorithm YOLOv5 Object Traffic Efficiency Fire YOLOv5 Attains
Modeling Adversarial Attack on Pre-trained Language Models as Sequential Decision Making
Xuanjie Fang, Sijie Cheng, Yang Liu, Wei Wang
Pre Trained Language Model Adversarial Perspective Language Model Adversarial Attack Sequential Decision Making
On the Importance of Backbone to the Adversarial Robustness of Object Detectors
Xiao Li, Hang Chen, Xiaolin Hu
Numerous Cutting Edge Backbone Robust Object Detection Object Detector Adversarial Robustness Adversarial Attack Importance Aware Deep Learning Based Object
Rapid Plug-in Defenders
Kai Wu, Yujian Betterest Li, Jian Lou, Xiaoyu Zhang, Handing Wang, Jing Liu
Adversarial Example Adversarial Training Adversarial Attack Transformer Based Adversarial Purification
Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL
Xiangyu Liu, Souradip Chakraborty, Yanchao Sun, Furong Huang
Adversarial Policy Provable Defense Step Attack Adversarial Attack Human Like RL

May 25, 2023

Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text
Ashim Gupta, Carter Wood Blum, Temma Choji, Yingjie Fei, Shalin Shah, Alakananda Vempala, Vivek Srikumar
Better Adversarial Robustness Adversarial Robustness Adversarial Perturbation Adversarial Attack Adversarial Input Text Modality
Adversarial Attacks on Leakage Detectors in Water Distribution Networks
Paul Stahlhofen, André Artelt, Luca Hermes, Barbara Hammer
Water Distribution Network Adversarial Attack Leakage Detector Model Robustness
IDEA: Invariant Defense for Graph Adversarial Robustness
Shuchang Tao, Qi Cao, Huawei Shen, Yunfan Wu, Bingbing Xu, Xueqi Cheng
Adversarial Graph Adversarial Example Adversarial Attack Adversarial Robustness
PEARL: Preprocessing Enhanced Adversarial Robust Learning of Image Deraining for Semantic Segmentation
Xianghao Jiao, Yaohua Liu, Jiaxin Gao, Xinyuan Chu, Risheng Liu, Xin Fan
Robust Adversarial Learning Semantic Segmentation Image Deraining Adversarial Prediction Adversarial Attack Adversarial Perturbation

May 24, 2023

How do humans perceive adversarial text? A reality check on the validity and naturalness of word-based adversarial attacks
Salijona Dyrmishi, Salah Ghamizi, Maxime Cordy
Adversarial Text Text Attack Reality Check Adversarial Example Word Level Adversarial Visual Naturalness Adversarial Attack Adversarial Perturbation Concurrent Validity
Frequency maps reveal the correlation between Adversarial Attacks and Implicit Bias
Lorenzo Basile, Nikos Karantzas, Alberto d'Onofrio, Luca Manzoni, Luca Bortolussi, Alex Rodriguez, Fabio Anselmi
Adversarial Attack Intrinsic Dimension Nonlinear Correlation Neural Network Implicit Bias

Adversarial Attack

Papers - Page 70

UMD: Unsupervised Model Detection for X2X Backdoor Attacks

Exploiting Explainability to Design Adversarial Attacks and Evaluate Attack Resilience in Hate-Speech Detection Models

From Adversarial Arms Race to Model-centric Evaluation: Motivating a Unified Automatic Robustness Evaluation Framework

Fourier Analysis on Robustness of Graph Convolutional Neural Networks for Skeleton-based Action Recognition

Membership Inference Attacks against Language Models via Neighbourhood Comparison

Two Heads are Better than One: Towards Better Adversarial Robustness by Combining Transduction and Rejection

Adversarial Attack On Yolov5 For Traffic And Road Sign Detection

Modeling Adversarial Attack on Pre-trained Language Models as Sequential Decision Making

On the Importance of Backbone to the Adversarial Robustness of Object Detectors

Rapid Plug-in Defenders

Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL

Adversarial Attacks on Online Learning to Rank with Click Feedback

DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution

Trust-Aware Resilient Control and Coordination of Connected and Automated Vehicles

Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text

Adversarial Attacks on Leakage Detectors in Water Distribution Networks

IDEA: Invariant Defense for Graph Adversarial Robustness

PEARL: Preprocessing Enhanced Adversarial Robust Learning of Image Deraining for Semantic Segmentation

How do humans perceive adversarial text? A reality check on the validity and naturalness of word-based adversarial attacks

Frequency maps reveal the correlation between Adversarial Attacks and Implicit Bias