Predictive Analytics and Threat Intelligence with AI and ML
Richard A. Young · Productivity Press eBooks · 2025
One of the most promising applications of Artificial Intelligence (AI) and Machine Learning (ML) in cybersecurity is the development of threat prediction models. These models allow organizations to proactively identify potential threats and vulnerabilities before they manifest into full-scale attacks. Traditional cybersecurity strategies have been largely reactive, focusing on detection and mitigation after a breach occurs. However, the advent of AI and ML has enabled a shift toward more predictive approaches, where emerging threats can be identified, analyzed, and neutralized in advance ( Figure 4.1 ). Figure 4.1 The benefits of automating AI in cybersecurity The diagram depicts the benefits of automating A I in cybersecurity, featuring a central circle labeled A I Benefits surrounded by six circles, each representing different advantages. Ongoing learning, improved vulnerability management, enhanced overall security posture, better detection and response, vast data volumes, and discovering unknown threats. https://www.w3.org/1999/xlink" content-type="black-white" xlink:href=" https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781003615026/390715e4-fe4d-4363-897f-f39dc1dd4197/content/fig4_1_B.tif "/>