AI-Driven Threat Detection in Cybersecurit
Bhanuprakash Madupati · Journal of Artificial Intelligence Machine Learning and Data Science · 2024
With the increasing complexity, changing trend and high non-linearity of techniques in exploring adversarial behaviours, Artificial Intelligence (AI) plays a significant role in current cybersecurity, which provides more advanced methodologies for discovering threat circumstances automatically, unlike static or semi-dynamic traditional intrusion detection systems.AI technologies like machine learning (ML) and deep learning (DL) can process large datasets in a few milliseconds and have emerged far stronger than traditional rule-based detection methods to detect new patterns or previously unseen threats, including zeroday attacks and advanced persistent threats.This paper uses the lead AI models used in threat detection (supervised learning unsupervised learning-and multiple approaches) to achieve better accuracy.AI-based systems have disrupted the cybersecurity landscape, but adversarial attacks, false positives, and data privacy remain challenges.This paper concludes that with in-depth insights into AI's current embodiments and shortcomings, future progress viz Explainable AI (XAI) and predictive models will likely define the cybersecurity landscape.