Applying Deep Reinforcement Learning for Detection of Internet-of- Things Cyber Attacks
Author:
Affiliation:
1. University of Tennessee, Knoxville,Department of Industrial and Systems Engineering,Knoxville,Tennessee,37830
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10099037/10098906/10099349.pdf?arnumber=10099349
Reference27 articles.
1. ToN_IoT: The Role of Heterogeneity and the Need for Standardization of Features and Attack Types in IoT Network Intrusion Data Sets
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3. Federated TON_IoT Windows Datasets for Evaluating AI-Based Security Applications
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5. Using Knowledge Graphs and Reinforcement Learning for Malware Analysis
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3. Detection of Malicious Threats Exploiting Clock-Gating Hardware Using Machine Learning;Sensors;2024-02-02
4. Binary Hunter–Prey Optimization with Machine Learning—Based Cybersecurity Solution on Internet of Things Environment;Sensors;2023-08-16
5. Improving Intrusion Detection in Internet of Things Networks with Feed-Forward Neural Networks Based on the UNSW-NB15 Dataset;2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT);2023-07-06
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