This paper presents a comprehensive literature review on Reinforcement Learning (RL) techniques used in Intrusion Detection Systems (IDS), Intrusion Prevention ...
Mar 10, 2023 · In this work, we applied a deep RL (DRL) framework in adversarial cyber-attack simulation to enhance cybersecurity.
Oct 17, 2024 · This article explores the application of reinforcement learning in various domains of cybersecurity, including intrusion detection systems, ...
Jun 13, 2019 · We touch on different vital as- pects, including DRL-based security methods for cyber-physical systems, autonomous intrusion detection ...
May 7, 2024 · This study suggests the Deep Reinforcement Learning-assisted Network Awareness Risk Perception and Prevention Model (DRL-NARPP) for detecting malicious ...
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Research into RL has been proven to have made a real contribution to the protection of cyberphysical distributed systems.
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In this paper, we propose a reinforcement learning algorithm with safe exploration and uses transfer learning to reduce the initial random exploration.
Our work provides a systematic view for understanding and solving decision-making problems in the application of reinforcement learning to cyber defense.
Sep 25, 2023 · In this paper, we design a safe reinforcement learning algorithm for network security applications to guide the learning agent to avoid exploring risky ...
Mar 15, 2024 · This paper suggests applying deep reinforcement learning (DRL), a deep framework, to simulate malicious cyberattacks and enhance cybersecurity.