AI-Driven Cybersecurity: The Double-Edged Sword of Automation and Adversarial Threats

Abstract

The use of Artificial Intelligence (AI) in cybersecurity functioning has brought in a new age of automated detection and reaction to threats, real-time response, and predictive defense. Nonetheless, such technological advance has become associated with numerous threats as malicious actors are turning to adversarial AI to circumvent defenses, adversarially train models, and implement advanced attacks. This paper critically observes the dual-use characteristic of AI in cybersecurity with both defense and offensive aspects of the phenomenon. Case studies combined with an examination of the literature can draw attention to the escalating arms race between those seeking to defend and those seeking to attack, showing the weaknesses of present AI systems when put under an adversarial input. The paper suggests an authoritative model of achieving adaptability, resilience, and ethically managed AI-based cybersecurity systems. By doing that, it highlights the necessity of organizations not only implementing AI, but also protecting themselves against it.