Definition and Scope
Data Loss Prevention (DLP) is a cybersecurity strategy and set of technologies designed to detect, monitor, and prevent unauthorized access, use, or transmission of sensitive data. Originating in the early 2000s, DLP has evolved from basic endpoint monitoring to cloud-native solutions integrated with SASE and SSE frameworks.
Core DLP Components
- Data Identification: Classifies sensitive data (e.g., PII, PHI, intellectual property) using regex, machine learning, or fingerprinting.
- Endpoint Protection: Monitors devices for unauthorized data transfers (e.g., USB, email).
- Network Monitoring: Inspects traffic across web, email, and cloud apps for policy violations.
- Cloud DLP: Secures SaaS, IaaS, and PaaS environments with API-based controls.
- Incident Response: Alerts, blocks, or encrypts data to mitigate breaches.
Why DLP Matters
With 80% of breaches involving data exfiltration (Verizon DBIR 2025), DLP is critical for compliance (GDPR, HIPAA, PCI-DSS) and protecting trade secrets. Modern DLP leverages AI to detect anomalies and integrates with zero-trust models for granular control.