InfoSec 101: Why Data Loss Prevention Is Important to Enterprise Defense

Mitigating insider threats. Insider threats, whether intentional or accidental, can be mitigated through DLP, which monitors and restricts data access and sharing based on predefined policies.

Ensuring compliance with regulations. Compliance is not the same as security, but it's a great way to provide a viable security baseline for organizations. DLP helps organizations adhere to data protection regulations, such as GDPR and HIPAA, by ensuring that sensitive data is handled in compliance with the law.

Safeguarding intellectual property. DLP is particularly important for tech companies and research institutions because it protects valuable intellectual property from theft or leaks.

Identification and classification of sensitive data. This principle involves identifying and classifying sensitive data within an organization, such as personally identifiable information (PII), financial data, intellectual property, and proprietary business data.

Policy creation and enforcement. DLP policies specify rules and actions — such as blocking data transfer, encrypting data, alerting administrators, or quarantining data for review — that are triggered when sensitive data is detected.

Content inspection and contextual analysis. Content inspection techniques analyze content to identify sensitive information using predefined patterns, regular expressions, and sometimes machine learning algorithms. Contextual analysis considers the context, such as user roles and permissions, in which data is being accessed or shared.

User and entity behavior analysis (UEBA). By incorporating behavioral analytics to understand normal patterns of data usage and user behavior, DLP solutions can detect anomalies that might indicate a data breach or insider threat.

Endpoint protection. Protecting data at endpoints (computers, laptops, mobile devices) means preventing users from copying, printing, or sharing sensitive data without proper authorization.

Cloud-based DLP monitors data activity in cloud environments and prevents data leaks in cloud storage and applications. Such solutions are designed to help organizations identify, classify, and protect sensitive data within their cloud environments.

Network-based DLP monitors network traffic to detect and prevent data leaks, ensuring that sensitive data in motion is protected by automatically encrypting it. This encryption helps safeguard the data as it moves throughout the network, providing increased visibility into its use, timing, and users involved.

Endpoint-based DLP is installed on individual devices and monitors data activity on those devices, focusing on monitoring and controlling the movement of sensitive data via file transfers, email communications, instant messaging, and Web browsing. For a remote workforce, priorities include ensuring that the devices have the proper permissions so that users or threat actors can't change the program, while still receiving and installing policy and program updates in a timely manner.