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Increased Accuracy in Blockchain-Based Intrusion Detection and Prevention System
  • Ahmed Aliyu,
  • Jinshuo Liu,
  • Ezekia Gilliard
Ahmed Aliyu
Wuhan University

Corresponding Author:[email protected]

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Jinshuo Liu
Wuhan University
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Ezekia Gilliard
Wuhan University
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Intrusion Detection and Prevention (IDPS) is a critical cybersecurity task that involves monitoring network traffic for malicious activity and taking appropriate action to stop it. However, insufficient training data or improperly chosen thresholds often limit the accuracy of such systems, resulting in high false positive rates. To improve the accuracy of an IDPS, blockchain technology can be used. Blockchain technology provides a secure, decentralized, immutable ledger that can track suspicious activity over time and identify intrusions globally. Security teams can use blockchain technology to create immutable records of suspicious activity, give users visibility into the system, and improve the accuracy of intrusion detection systems. In this paper, we propose a novel methodology to improve the accuracy of blockchain-based intrusion detection and prevention systems, which is based on combining different intrusion detection algorithms and using a blockchain-integrated architecture. Our experimental results show that the proposed system significantly increases the accuracy while reducing the false positive rate, opening up new opportunities for the development of highly accurate networks.
07 Jun 2023Submitted to Electronics Letters
09 Jun 2023Submission Checks Completed
09 Jun 2023Assigned to Editor
13 Jun 2023Reviewer(s) Assigned
28 Jun 2023Review(s) Completed, Editorial Evaluation Pending
03 Jul 2023Editorial Decision: Revise Major
09 Jul 20231st Revision Received
11 Jul 2023Submission Checks Completed
11 Jul 2023Assigned to Editor
11 Jul 2023Review(s) Completed, Editorial Evaluation Pending
12 Jul 2023Editorial Decision: Accept