Review of AI and machine learning applications to predict and Thwart cyber-attacks in real-time
1 Indiana Wesleyan University, USA.
2 Access Bank Plc, Nigeria.
3 Sanctus Maris Concepts, Nigeria Ltd.
4 Independent Researcher, Port Harcourt, Rivers State, Nigeria.
5 Department of Information Management, Ahmadu Bello University, Zaria, Nigeria.
Review Article
Magna Scientia Advanced Research and Reviews, 2024, 10(01), 312–320
Article DOI: 10.30574/msarr.2024.10.1.0037
Publication history:
Received on 08 January 2024; revised on 15 February 2024; accepted on 17 February 2024
Abstract:
The contemporary cybersecurity landscape demands innovative solutions to combat the relentless evolution of cyber threats. Traditional approaches are facing unprecedented challenges, compelling a paradigm shift towards the integration of Artificial Intelligence (AI) and Machine Learning (ML). This paper meticulously explores the potential of AI and ML to fortify real-time cybersecurity, with a focus on the swift prediction and mitigation of cyber-attacks. Against the backdrop of an escalating threat landscape, this paper propels the inquiry into advanced technologies to fortify cybersecurity. The limitations of traditional methodologies underscore the urgency of investigating the efficacy of AI and ML in reinforcing defense mechanisms. This paper endeavors to comprehensively investigate the role of AI and ML in real-time cybersecurity. It places a distinct emphasis on their potential to predict and thwart cyber-attacks promptly. The exploration encompasses diverse dimensions, ranging from the intricacies of model complexity to crucial considerations in security, ethics, and emerging trends. Structured around a robust framework, the exploration encompasses comprehensive research directions. These include the imperative to enhance explainability, address vulnerabilities to adversarial attacks, foster collaboration between humans and AI, and develop quantum-resistant cryptographic solutions. The paper navigates through the intricate technical, organizational, and ethical dimensions inherent in the implementation of AI and ML in real-time cybersecurity. The findings of this exploration illuminate both the promises and challenges associated with the integration of AI and ML in cybersecurity. Ethical considerations, vulnerabilities to adversarial attacks, and the exigency for quantum-resistant cryptography emerge as critical areas necessitating nuanced attention and exploration. This paper envisions a future where the fusion of human expertise with the capabilities of AI and ML results in the creation of resilient and adaptive cybersecurity ecosystems. The delineated research directions serve not only as a comprehensive roadmap for ongoing innovation but also as a foundational guide to effectively integrate AI and ML in safeguarding our digital realm against the ever-evolving landscape of cyber threats.
Keywords:
AI; Machine; Applications; Thwart; Cyber-attacks; Real-Time.
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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