Enhancing Cybersecurity through AI and ML: Strategies, Challenges, and Future Directions

Roshanaei, Maryam and Khan, Mahir R. and Sylvester, Natalie N. (2024) Enhancing Cybersecurity through AI and ML: Strategies, Challenges, and Future Directions. Journal of Information Security, 15 (03). pp. 320-339. ISSN 2153-1234

[thumbnail of jis2024153_37801018.pdf] Text
jis2024153_37801018.pdf - Published Version

Download (544kB)

Abstract

The landscape of cybersecurity is rapidly evolving due to the advancement and integration of Artificial Intelligence (AI) and Machine Learning (ML). This paper explores the crucial role of AI and ML in enhancing cybersecurity defenses against increasingly sophisticated cyber threats, while also highlighting the new vulnerabilities introduced by these technologies. Through a comprehensive analysis that includes historical trends, technological evaluations, and predictive modeling, the dual-edged nature of AI and ML in cybersecurity is examined. Significant challenges such as data privacy, continuous training of AI models, manipulation risks, and ethical concerns are addressed. The paper emphasizes a balanced approach that leverages technological innovation alongside rigorous ethical standards and robust cybersecurity practices. This approach facilitates collaboration among various stakeholders to develop guidelines that ensure responsible and effective use of AI in cybersecurity, aiming to enhance system integrity and privacy without compromising security.

Item Type: Article
Subjects: Institute Archives > Computer Science
Depositing User: Managing Editor
Date Deposited: 06 Jul 2024 09:34
Last Modified: 06 Jul 2024 09:34
URI: http://eprint.subtopublish.com/id/eprint/4394

Actions (login required)

View Item
View Item