DLP Fundamentals

Data Loss Prevention (DLP) detects and prevents unauthorized data exfiltration. DLP identifies sensitive data through content inspection, monitors data movement across networks, endpoints, and cloud, and enforces policies to prevent accidental or malicious data loss.

DLP Components

DLP architecture includes data discovery identifying sensitive data locations, policy engine defining protection rules, monitoring agents on networks/endpoints/cloud, and enforcement actions from alerting to blocking data transfers.

Detection Techniques

DLP detects sensitive data using pattern matching (regex for SSN, credit cards), keyword searches, document fingerprinting, machine learning classification, and contextual analysis combining multiple signals for accurate detection with minimal false positives.

DLP Deployment Models

Deploy DLP at network perimeter monitoring outbound traffic, on endpoints protecting data in use, in email gateways preventing data leakage, and in cloud applications (CASB) securing SaaS environments.

Implementation Strategy

Start with discovery to understand data locations and flows, define data classification, create policies starting with monitoring, educate users, gradually enforce blocking, and continuously tune policies reducing false positives while improving coverage.