Blockchain-Aided Intrusion Detection in Marine Tactical Network Using Reinforcement Learning 


Vol. 50,  No. 12, pp. 1937-1957, Dec.  2025
10.7840/kics.2025.50.12.1937


PDF Full-Text
  Abstract

Marine Tactical Networks (MTNs) are essential for secure maritime operations, but are highly susceptible to cyber threats. Traditional Intrusion Detection Systems (IDS) often struggle to adapt to the dynamic and complex nature of MTNs. This paper introduces a Blockchain-Aided Intrusion Detection System (BAE-RL), which integrates reinforcement learning (RL) and blockchain technology to improve threat detection and security. The BAE-RL framework is unique in its use of multi-agent adversarial RL, where a defender agent learns to detect attacks by interacting with a simulated attacker agent. This adversarial setup enhances the system’ s ability to identify novel and evolving threats. Additionally, blockchain integration ensures the integrity and immutability of detection data, preventing tampering and ensuring transparency. Experimental results show that the proposed framework outperforms traditional IDS, achieving 80.16% and 95.9% accuracy on the NSL-KDD and AWID datasets, respectively. The BAE-RL framework offers a robust, adaptive, and secure solution for intrusion detection in MTNs.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Related Articles
  Cite this article

[IEEE Style]

M. R. Subhan, M. M. Alam, M. Golam, M. F. Rahaman, T. Jun, "Blockchain-Aided Intrusion Detection in Marine Tactical Network Using Reinforcement Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 12, pp. 1937-1957, 2025. DOI: 10.7840/kics.2025.50.12.1937.

[ACM Style]

Md Raihan Subhan, Md Mahinur Alam, Mohtasin Golam, Md Facklasur Rahaman, and Taesoo Jun. 2025. Blockchain-Aided Intrusion Detection in Marine Tactical Network Using Reinforcement Learning. The Journal of Korean Institute of Communications and Information Sciences, 50, 12, (2025), 1937-1957. DOI: 10.7840/kics.2025.50.12.1937.

[KICS Style]

Md Raihan Subhan, Md Mahinur Alam, Mohtasin Golam, Md Facklasur Rahaman, Taesoo Jun, "Blockchain-Aided Intrusion Detection in Marine Tactical Network Using Reinforcement Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 12, pp. 1937-1957, 12. 2025. (https://doi.org/10.7840/kics.2025.50.12.1937)
Vol. 50, No. 12 Index

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)






pISSN : 1226 - 4717
eISSN : 2287 - 3880