This practical guide shows how to build a Data Loss Prevention program that fits real business needs.
It covers objectives, risk appetite, data classification, enterprise discovery, risk registers, policy design, and DLP architecture across endpoints, networks, cloud services, email, SaaS, databases, and collaboration tools.
You'll learn to create accurate detection rules, control data transfers, protect managed and unmanaged devices, integrate DLP with identity and security operations, and investigate insider exfiltration.
The book also covers privacy, regulatory evidence, rollout planning, user adoption, false-positive reduction, operational runbooks, generative AI, and emerging exfiltration risks.
It's written for security, privacy, IT, legal, compliance, and business leaders who need a measurable DLP program-not a collection of disconnected tools and alerts.