Network Intrusion Detection and Mitigation Using Hybrid Optimization Integrated Deep Q Network-Reference-Cited by-同舟云学术

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Network Intrusion Detection and Mitigation Using Hybrid Optimization Integrated Deep Q Network

Published:2022-07-07 Issue: Volume: Page:1-17
ISSN:0196-9722
Container-title:Cybernetics and Systems
language:en
Short-container-title:Cybernetics and Systems

Author:

Emil Selvan G. S. R.¹,Daniya T.²,Ananth J. P.³,Suresh Kumar K.⁴

Affiliation:

1. Department of Computer Science and Engineering, Thiagarajar College of Engineering, Madurai, India

2. Department of Information Technology, GMR Institute of Technology, Rajam, India

3. Department of CSE, Sri Krishna College of Engineering and Technology, Coimbatore, India

4. Department of Information Technology, Saveetha Engineering College, Chennai, India

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Information Systems,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/01969722.2022.2088450

Reference35 articles.

1. Deep Q-Learning Based Reinforcement Learning Approach for Network Intrusion Detection

2. A Feature Selection Model for Network Intrusion Detection System Based on PSO, GWO, FFA and GA Algorithms

3. A Hybrid Model Using Bio-Inspired Metaheuristic Algorithms for Network Intrusion Detection System

4. A Modified Grey Wolf Optimization Algorithm for an Intrusion Detection System

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1. Review of intrusion detection system in cyber‐physical system based networks: Characteristics, industrial protocols, attacks, data sets and challenges;Transactions on Emerging Telecommunications Technologies;2024-08-19

2. Network Information Security Monitoring Under Artificial Intelligence Environment;International Journal of Information Security and Privacy;2024-06-06

3. A review of spider monkey optimization: modification and its biomedical application;International Journal on Interactive Design and Manufacturing (IJIDeM);2023-12-22

4. Deep Reinforcement Learning for intrusion detection in Internet of Things: Best practices, lessons learnt, and open challenges;Computer Networks;2023-11

5. Deep Reinforcement Learning for Intrusion Detection in Internet of Things: Best Practices, Lessons Learnt, and Open Challenges;2023

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