Quantal Response-Based Adversarial Reinforcement Learning for Smart Grid Attack-Defense Game With Bounded Rationality Evolution

Resilient Multi-Agent Deep Reinforcement Learning for Automatic Generation Control Under Adversarial Perturbations

Building A Cyber-Resilient Smart Grid With Artificial Intelligence-Driven Defense: Protecting Smart Grids Against Coordinated Cyberattacks

Modern power grids are evolving into highly interconnected cyber-physical systems (CPSs), enabling advanced monitoring, automation, and control. While these innovations improve efficiency and reliability, they also introduce new vulnerabilities. A well-devised single cyberattack can cascade across the grid, disrupting...

Dynamic defense strategies for cyber-physical systems using Stackelberg games and deep reinforcement learning in discrete and continuous time

This study presents a dual-domain defense framework that combines Stackelberg game theory with Deep Reinforcement Learning that offers a robust, adaptable toolset for CPS defense by clarifying the trade-offs between temporal abstractions in nonlinear and dynamic environments.

TIGER: An Open-Source Cyber-Threat Intelligence Game Environment for Reinforcement Learning

T tiger, an open-source Threat Intelligence Game Environment for Reinforcement learning-based agents to be trained and evaluated toward the optimisation of the costs-benefit trade-off associated with realistic ML-driven cyber-defence life-cycles is presented.

Multi-Agents Assisted Autonomous Breach and Attack Simulation Framework in Power Information System

An end-to-end red teaming framework built upon cooperative multi-agent collaboration is introduced, enabling full life-cycle attack simulation in power information systems and effectively identifying deeply hidden vulnerabilities within complex power information networks.

Quantum Reinforcement Learning Agent for Adaptive Firewall Rule Optimization Under Dynamic Attacks

As attacks grow in sophistication, the requirements for intelligent and adaptive security structures that can make real-time decisions on whether to defend or not, exceed what can be achieved with a rule-based approach. This paper aims to explore a Cyber Security system that uses a Quantum Deep Q-Network (QDQN) framewo...