Data Loss Prevention Basics

Data loss prevention software detects potential data breaches, data ex-filtration transmissions, and protect this data by monitoring, detecting and blocking sensitive data while at rest (storage data in hard drive), in use (being used at the endpoint), and in motion (data traveling across the network).

In fact, DLP allows companies to identify, classify, and protect data to keep it secure. One of the most important traits of DLP is detecting 100+ types of sensitive data, such as personally identifiable information (PII), credentials, and more from exfiltrating the organizational computer stored system. This security measure is required and is put in place for organizations -for many reasons- specifically, not exposing individual personal and health information into the black market. This kind of protection helps the organization to save money in even lawsuits as individuals can take a judicial action against the company if his personal information is breached and posted in the black market. Also, it’s good to know that DLP blocks the extraction of sensitive data, which is why organizations use it for internal security and compliance with regulations like HIPAA compliance in the health sector, for protecting personal health information (PHI). 

Nowadays, as cyber threats keep increasing in sophisticated manner, it is crucial for organizations to be proactive in defending these breaches. Furthermore, DLP software enables businesses to detect data loss, as well as prevent unauthorized transfers of data outside the organization, and the illicit destruction of sensitive information or PII.

This is how DLP allows organizations to:

Ø  Identify sensitive information across multiple on end-users and cloud-based systems.

Ø  Prevent the accidental sharing of sensitive data.

Ø  Monitor and protect sensitive information.

Ø  Educate users on how to stay compliant.

When implementing DLP in systems, it protects businesses by identifying sensitive information, then using a deeper content analysis to detect and prevent possible data leaks. This content analysis uses methods like keyword matches, regular expressions, and internal functions to recognize content that matches the enterprise’s DLP policy. As a result, organizations can identify, monitor, and automatically prevent the theft or exposure of sensitive information such as credit card numbers and PII, intellectual property (IP) like profit or non-organization business secrets, or even government secrets, that could generate considerable impact on finances or self-reputation if they get stolen.