AI-Driven Threat Detection and Prevention

Abstract

The rapid changes in the cyber threat landscape in the digital age have changed the design of security mechanisms to support proactive and adaptive security capabilities that can detect, predict, and respond to attacks in real time. This chapter discusses the potential of integrating Artificial Intelligence (AI), Machine Learning (ML), and Predictive Intelligence for cybersecurity through proactive threat detection and prevention. The chapter covers how AI-based predictive models can analyze vast and complex (and rich) data and identify hidden/novel attack patters, detect anomalies for faster incident response, and features supervised, unsupervised, and deep learning models for intrusion detection, malware analysis, and phishing prevention as well as predictive intelligence to help prevent zero-day attacks and other new avenues of security threats. Examples of real-world applications and case studies show how AI-powered solutions can dramatically cut down false-positives, leap-frog situational awareness, and increase resiliency and preparedness for an organization.