Artificial Intelligence for Cybersecurity: Enhancing Threat Detection and Response

Abstract

Level of sophistication increases and the frequency of cyber-attacks, too, AI has become a cornerstone in enhancing cybersecurity. Traditional cybersecurity measures frequently fail to visualize a real-time discovery of sophisticated multivector threats. This brings in an urgent need for a new solution. The following article discusses the application of AI in enhancement capability to detect and respond to cybersecurity threats. We revise the literature and methodologies that explain how AI- powered models and algorithms allow proactive identification of threats, rapid responses, and full insights into the nature of cyber-attacks. We propose a hybrid model that combines ML-DL methodologies to enhance the efficiency of the threat detection process while reducing the reaction time with the goal of eventually strengthening cybersecurity defenses in dynamic contexts.