Adversary Agent

Adversary agents represent a crucial area of research focusing on how malicious actors can exploit vulnerabilities in artificial intelligence systems, particularly machine learning models. Current research investigates various attack strategies, including data poisoning, model inversion, and adversarial examples, across diverse model architectures like deep neural networks and reinforcement learning agents, often employing game-theoretic frameworks and adversarial training techniques to analyze and mitigate these threats. Understanding and defending against adversary agents is vital for ensuring the safety, reliability, and trustworthiness of AI systems in critical applications, ranging from cybersecurity to healthcare and finance.

Papers

October 26, 2024

Classification under strategic adversary manipulation using pessimistic bilevel optimisation
David Benfield, Stefano Coniglio, Martin Kunc, Phan Tu Vuong, Alain Zemkoho
Classification Code Adversarial Learning Bilevel Optimization Adversary Agent Optimisation Problem Non Convexity

October 22, 2024

Optimal Robust Estimation under Local and Global Corruptions: Stronger Adversary and Smaller Error
Thanasis Pittas, Ankit Pensia
Error Correction Adversary Agent Optimal Estimation Common Corruption Contamination Detection Robust Statistic Robust Inference Class Outlier

October 21, 2024

Patrol Security Game: Defending Against Adversary with Freedom in Attack Timing, Location, and Duration
Hao-Tsung Yang, Ting-Kai Weng, Ting-Yu Chang, Kin Sum Liu, Shan Lin, Jie Gao, Shih-Yu Tsai
Deep Reinforcement Learning Multi Robot Adversary Agent Timing Analysis Patrolling Strategy Long Duration

October 20, 2024

PEAS: A Strategy for Crafting Transferable Adversarial Examples
Bar Avraham, Yisroel Mirsky
Adversarial Example Supervised ImageNet Adversarial Perturbation Strategy Logic Adversary Agent

June 20, 2024

Adversaries Can Misuse Combinations of Safe Models
Erik Jones, Anca Dragan, Jacob Steinhardt
Artificial Intelligence System Strategic Manipulation Adversary Agent Model Safety Malicious Data

June 17, 2024

Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness
Maayan Ehrenberg, Roy Ganz, Nir Rosenfeld
Adversarial Training Adversarial Robustness Adversarial Learning Adversary Agent Model Accuracy Institutional Incentive

May 29, 2024

Resilient Average Consensus with Adversaries via Distributed Detection and Recovery
Liwei Yuan, Hideaki Ishii
Data Detection Multi Agent System Prompt Recovery Adversary Agent Multi Agent Network Average Consensus Averaging Algorithm

March 15, 2024

Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries
Swetha Ganesh, Jiayu Chen, Gugan Thoppe, Vaneet Aggarwal
Policy Gradient Federated Reinforcement Learning Adversary Agent Adversarial Agent Global Convergence Guarantee

February 20, 2024

Bounding Reconstruction Attack Success of Adversaries Without Data Priors
Alexander Ziller, Anneliese Riess, Kristian Schwethelm, Tamara T. Mueller, Daniel Rueckert, Georgios Kaissis
Differential Privacy Sensitive Data Adversarial Scenario Upper Bound Adversary Agent Reconstruction Attack Data Driven Prior

February 13, 2024

Regret Minimization in Stackelberg Games with Side Information
Keegan Harris, Zhiwei Steven Wu, Maria-Florina Balcan
Regret Minimization Adversary Agent Optimal Strategy Stackelberg Game Adversarial Setting Side Information

February 6, 2024

Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses
Hao Fang, Yixiang Qiu, Hongyao Yu, Wenbo Yu, Jiawei Kong, Baoli Chong, Bin Chen, Xuan Wang, Shu-Tao Xia, Ke Xu
Timely Survey High Fidelity PRIvacy Leakage Model Inversion Attack Adversary Agent Model Inversion Private Training

November 13, 2023

Transpose Attack: Stealing Datasets with Bidirectional Training
Guy Amit, Mosh Levy, Yisroel Mirsky
Deep Neural Network Data Set Adversary Agent Bidirectional Training Public Model Data Exfiltration

October 28, 2023

Large Language Models Are Better Adversaries: Exploring Generative Clean-Label Backdoor Attacks Against Text Classifiers
Wencong You, Zayd Hammoudeh, Daniel Lowd
Adversarial Example Backdoor Attack Attack Success Rate Adversary Agent Text Classifier Clean Label Backdoor Attack Textual Backdoor Attack Clean Label Attack

October 12, 2023

October 5, 2023

Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally
Shawqi Al-Maliki, Adnan Qayyum, Hassan Ali, Mohamed Abdallah, Junaid Qadir, Dinh Thai Hoang, Dusit Niyato, Ala Al-Fuqaha
Deep Neural Network Adversarial Example Adversarial Learning Adversary Agent Target Amazon Ally Social AI

September 27, 2023

Automatic Feature Fairness in Recommendation via Adversaries
Hengchang Hu, Yiming Cao, Zhankui He, Samson Tan, Min-Yen Kan
Adversarial Perturbation Effective Recommendation Adversary Agent Fairness Aware Generalizable Feature Space Bias Imbalanced Training

September 26, 2023

Gray-box Adversarial Attack of Deep Reinforcement Learning-based Trading Agents
Foozhan Ataiefard, Hadi Hemmati
Deep Reinforcement Learning Native Robustness Deep Reinforcement Robust Reinforcement Learning Deep RL Adversary Agent Gray Box

July 19, 2023

Rethinking Backdoor Attacks
Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry
Backdoor Attack Adversary Agent Effective Backdoor

June 27, 2023

Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets
Yimu Wang, Dinghuai Zhang, Yihan Wu, Heng Huang, Hongyang Zhang
Adversarial Attack Long Term Cooperation Competition Platform Adversary Agent Monotone Adversary Robust Network Double Robustness Matrix Domination