What type of protection does Zscaler's DLP primarily provide based on sequences of sensitive data?

Zscaler's Data Loss Prevention (DLP) primarily offers protection by recognizing and responding to sequences of sensitive data through exact matches. This approach allows organizations to identify and control specific patterns that signify sensitive information, such as Social Security numbers, credit card details, or intellectual property. By focusing on exact matches, DLP can more effectively prevent unauthorized access or transmission of this sensitive data, ensuring compliance with regulatory requirements and organizational policies.

In this context, while real-time communication is essential for swift data handling and response, it does not specifically address the core of DLP functionality, which is centered on identifying sensitive data. Similarly, policy enforcement relates to how rules are applied in the DLP framework but does not directly point to the mechanics of detecting sensitive data sequences. Content analysis also plays a role in broader data inspection strategies, yet it extends beyond just matching sequences and includes the evaluation of the context and structure of the data. Thus, the focus on exact matches is what sets this protection mechanism apart as the primary function of Zscaler’s DLP.