AI Cybersecurity for Threat Intelligence

AI Cybersecurity for Threat Intelligence: Automate Threat Hunting, Enrich IOCs, and Cut Detection Time with Machine Learning and LLMs

Your SOC is drowning in alerts, threat reports, and fragmented signals while attackers move faster every day. Manual triage can't keep up, false positives burn analyst hours, and critical indicators get buried in noise. If your team is still piecing together threats by hand, you're already behind.

AI Cybersecurity for Threat Intelligence gives you a practical, production-focused path to modern defense. This book shows you how to build AI-assisted pipelines that collect, normalize, and enrich security data; extract high-value intelligence from unstructured reports; and drive faster, smarter detection across SIEM and SOAR workflows. You'll learn how to apply machine learning for anomaly detection, use LLMs for IOC extraction and threat report classification, and operationalize automation with governance, metrics, and feedback loops that improve over time.

By reading this book, you'll gain the ability to:

• Automate threat hunting workflows that scale with your environment

• Enrich IOCs with context that improves analyst decisions

• Reduce alert fatigue and prioritize real risk faster

• Deploy ML and LLM pipelines that integrate into existing security stacks

• Improve MTTD and MTTR with measurable, repeatable processes

• Build auditable, human-centered AI operations your team can trust

Want to stop chasing alerts and start running an intelligence-driven security program? Get your copy today and build a threat intelligence engine that helps your team detect earlier, respond faster, and defend with confidence.