Zhang, Z., Hamadi, H.A., Damiani, E., Yeun, C.Y. and Taher, F. (2022) Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research. IEEE Access, 10, 93104-93139.
https://doi.org/10.1109/access.2022.3204051

has been cited by the following article:

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

  AUTHORS: Maryam Roshanaei, Mahir R. Khan, Natalie N. Sylvester

  KEYWORDS: Artificial Intelligence, Machine Learning, Cybersecurity, Data Privacy and Security, Ethical Standards

  JOURNAL NAME: Journal of Information Security, Vol.15 No.3, July 5, 2024

  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.