Novel Intrusion Detection Strategies With Optimal Hyper Parameters for Industrial Internet of Things Based on Stochastic Games and Double Deep <i>Q</i>-Networks-Reference-Cited by-同舟云学术

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Novel Intrusion Detection Strategies With Optimal Hyper Parameters for Industrial Internet of Things Based on Stochastic Games and Double Deep Q-Networks

Published:2024-09-01 Issue:17 Volume:11 Page:29132-29145
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Yu Shoujian¹^ORCID,Wang Xuan¹^ORCID,Shen Yizhou²^ORCID,Wu Guowen¹^ORCID,Yu Shui³^ORCID,Shen Shigen⁴^ORCID

Affiliation:

1. School of Computer Science and Technology, Donghua University, Shanghai, China

2. School of Computing, Newcastle University, Newcastle upon Tyne, U.K.

3. School of Computer Science, University of Technology Sydney, Sydney, NSW, Australia

4. School of Information Engineering, Huzhou University, Huzhou, China

Funder

Zhejiang Provincial Natural Science Foundation of China

Huzhou Science and Technology Planning Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10643444/10540246.pdf?arnumber=10540246

Reference47 articles.

1. AI-Enabled Space-Air-Ground Integrated Networks: Management and Optimization

2. Deep Q-Network-Based Open-set Intrusion Detection Solution for Industrial Internet of Things

3. A Deep Neural Collaborative Filtering Based Service Recommendation Method with Multi-Source Data for Smart Cloud-Edge Collaboration Applications

4. Computation Offloading Method Using Stochastic Games for Software-Defined-Network-Based Multiagent Mobile Edge Computing

5. Joint Semantic Transfer Network for IoT Intrusion Detection

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