The Role of Explainable AI in cyber threat intelligence: Enhancing transparency and trust in security systems
1 Department of Computer Science, American International University-Bangladesh.
2 Department of Computer Science, Maharishi International University, Iowa, USA.
3 Department of Applied Physics, Electronics & Communication Engineering, University of Dhaka.
4 Department of Computer Science, American International University-Bangladesh.
5 Department of Computer Science & Engineering, Daffodil International University Dhaka Bangladesh.
6 Department of Computer Science & Engineering, Rajshahi University of Engineering & Technology (RUET), Bangladesh.
Research Article
World Journal of Advanced Research and Reviews, 2025, 23(02), 2897-2907
Article DOI: 10.30574/wjarr.2024.23.2.2404
Publication history:
Received on 30 June 2024; revised on 08 August 2024; accepted on 10 August 2024
Abstract:
XAI technology transforms cybersecurity by enabling transparent, secure systems that gain users' trust in AI threat information processes. This research examines how XAI improves cybersecurity systems through CTI by enhancing security models' interpretability and decision-making capabilities based on AI algorithms. The research evaluates how XAI addresses trust problems in typical AI systems because of their "black box" operation. Security frameworks with XAI components enhance user reliability and defensive quality by improving detection methods and response capabilities. Experts have confirmed that transparent artificial intelligence models increase trust between security professionals, policymakers, and organizational units. XAI is vital in modern cybersecurity developments because it strengthens organizational protection while improving decision choices. This study provides reasonable recommendations for industry stakeholders and academic institutions to develop explainable AI strategies for future cybersecurity application development.
Keywords:
XAI; trust; Cybersecurity; Threat detection; Decision-making; Transparency; Threat Intelligence
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0