Harnessing Artificial Intelligence for Proactive Identification of Zero-Day Vulnerabilities in Cybersecurity Systems - Pires, Maria Fernanda (MZ Journal of Artificial Intelligence, 2024)
As technology continues to evolve at an unprecedented pace, so do the threats posed by cyber adversaries. Zero-day vulnerabilities—flaws in software that are unknown to the vendor and exploited by attackers before a patch is available—pose significant risks to cybersecurity systems. Traditional approaches to vulnerability detection often rely on signature-based methods and manual analysis, which can be insufficient in rapidly identifying these emerging threats. This paper explores the potential of artificial intelligence (AI) in the proactive identification of zero-day vulnerabilities, discussing various AI techniques, their implementation, and their effectiveness in enhancing cybersecurity.