AI and Cybersecurity: Collaborator or Confrontation

9 pages•Published: March 21, 2024

Abstract

Artificial Intelligence (AI) is and has been rapidly transforming the landscape of cybersecurity as we know it, serving as a double-edged sword. On one side, AI systems can act as your ally, doing tasks like fortifying defense mechanisms and automating complex threat detection or intrusion detection systems. Machine learning models can sift through large amounts of data, identifying anomalies that could indicate a breach or malicious activity, which is often faster and more accurate than a human could be. This capability makes it possible to proactively counteract threats, minimizing any potential cyber issues. On the other hand, the power of AI can be easily weaponized by an adversary, becoming a potential threat actor. Sophisticated cybercriminals can use AI to craft advanced evasive malware and launch automated attacks. Techniques like using machine learning from an adversary perspective allow them to design inputs specifically intended to deceive AI-powered security systems. So as AI systems become smarter, do the tools and tactics used by adversaries looking to exploit them. This duality of AI in cybersecurity is an important relevance to professionals in the field. The discipline of a cybersecurity professional is constantly evolving in response to new strategies of the adversary. Professionals must be skilled at utilizing AI’s capabilities and limiting its weaknesses as it becomes more and more integrated into security infrastructure. Not only must the newest technology be used, but it must also be understood in terms of its ramifications, potential risks, and the constantly shifting dynamics between defenders and attackers. Staying ahead of the competition on the AI-enhanced cyber-warfare battlefield requires constant learning, adaptation, and persistence. In this paper, the discussion pivots around a central question: Is AI in cybersecurity a friend, a foe, or perhaps both?

Keyphrases: AI-based security systems, NIST, Zero Trust Security framework

In: Ajay Bandi, Mohammad Hossain and Ying Jin (editors). Proceedings of 39th International Conference on Computers and Their Applications, vol 98, pages 150--158

Links:	https://easychair.org/publications/paper/Brmj
	https://doi.org/10.29007/q3md