What type of data classification is used to protect sensitive information?

Classifying data based on its confidentiality and the impact of its disclosure is a fundamental approach to ensuring that sensitive information is adequately protected. This method typically involves categorizing data into levels such as public, internal, confidential, and sensitive, which helps organizations determine appropriate handling, access, and security measures based on the potential consequences of unauthorized access or disclosure.

For instance, sensitive information, such as personal identifiable information (PII) or trade secrets, requires stricter controls and protection measures compared to less sensitive data. By assessing the confidentiality of information and understanding the implications of its compromise, organizations can implement tailored security policies, access controls, and monitoring systems to safeguard their most critical assets.

In contrast, methods like classifying data based on color coding, encryption level, or age do not effectively address the core issue of data sensitivity and its implications. While encryption levels are essential for securing data, they don't inherently classify the data or consider the potential impact of its unauthorized disclosure. Similarly, age-based classification might help manage data lifecycle but is irrelevant to the sensitivity and protective needs of the data itself.