Data loss prevention software

Data loss prevention (DLP) software detects the unauthorized transmission or disclosure of sensitive data and prevents their occurrence, including data in motion (across networks), at rest (in storage), or in use (on endpoints). DLP systems have traditionally relied upon a variety of classification and enforcement mechanisms to reduce the risk of data leakage but increasingly incorporate machine learning and behavioral analytics to enhance detection accuracy. The range of environments in which DLP is used today has widened to include on-premises systems, cloud applications, and hybrid environments.

The terms "data loss" and "data leak" are related and are often used interchangeably. Data loss incidents turn into data leak incidents when media containing sensitive information are lost and then acquired by an unauthorized party. However, a data leak is possible without losing the data on the originating side. Other terms associated with data leakage prevention include information leak detection and prevention (ILDP), information leak prevention (ILP), content monitoring and filtering (CMF), information protection and control (IPC) and extrusion prevention system (EPS), as opposed to an intrusion prevention system.