Binary bat algorithm based feature selection with deep reinforcement learning technique for intrusion detection system-Reference-Cited by-同舟云学术

Binary bat algorithm based feature selection with deep reinforcement learning technique for intrusion detection system

Published:2023-06-08 Issue:15 Volume:27 Page:10777-10788
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Priya S.,Kumar K. Pradeep Mohan

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s00500-023-08678-9.pdf

Reference24 articles.

1. Akila S, Christe SA (2022) A wrapper based binary bat algorithm with greedy crossover for attribute selection. Expert Syst Appl 187:115828

2. Alavizadeh H, Alavizadeh H, Jang-Jaccard J (2022) Deep Q-learning based reinforcement learning approach for network intrusion detection. Computers 11(3):41

3. Alawsi ASS, Kurnaz S (2022) Quality of service system that is self-updating by intrusion detection systems using reinforcement learning. Appl Nanosci 13:1–8

4. Bouhamed O, Bouachir O, Aloqaily M, Al Ridhawi I (2021) Lightweight ids for uav networks: a periodic deep reinforcement learning-based approach. In: 2021 IFIP/IEEE international symposium on integrated network management (IM). IEEE. pp 1032–1037

5. Caminero G, Lopez-Martin M, Carro B (2019) Adversarial environment reinforcement learning algorithm for intrusion detection. Comput Netw 159:96–109

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