Resources are prioritized based on their classification, criticality, and business value.

Data classification can be used to give data processors a quick view of how critical data is and how data should be processed and protected.

The data categories used and the corresponding security levels are defined. The category of information is defined by analyzing the confidentiality, integrity and availability of the information in question, as well as any other requirements. Each level is given a clear and descriptive name.

Data classifications can be, for example, the following:

• disclosure of information does not cause harm (PUBLIC)
• disclosure of information causes slight inconvenience or minor operational annoyance (CONFIDENTIAL)
• disclosure of information has significant short-term effects on operations or tactical objectives (LIMITED)
• disclosure of information has serious implications for long-term strategic objectives or jeopardizes the very existence of the organization (PROHIBITED)

CONFIDENTIAL paper information may require e.g. the following protections:

• Locked cabinet
• Trusted transfer partner
• Sealed envelopes
• Safe disposal process

CONFIDENTIAL electronic information may require e.g. the following protections:

• Use the selected encryption level
• Password protection
• Safe disposal process
• More limited access rights

The dataset owners (or the owners of the related information asset, such as a data store or data system) are responsible for the classifications of the datasets and the correspondence of the classification to the definitions of the classes.

The owner updates the data classification over the life cycle of the asset according to variations in its value, sensitivity, and criticality.

An organization must classify its information assets, such as information systems, data, units, key personnel, and other assets to be protected (e.g., equipment), according to priorities. Prioritization can be done, for example, based on the requirements for confidentiality, integrity, and availability of the information being processed.

Data Loss Prevention (DLP) policies can be used to protect sensitive data from accidental or intentional disclosure. Policies can alert, for example, when they detect sensitive data (such as personal identification numbers or credit card numbers) in email or another data system to which they would not belong.

The organization defines DLP policies related to endpoints in a risk-based manner, taking into account the data classification of the processed data.

The DLP system aims to prevent the loss or leakage of sensitive data. The system can be used to prevent unwanted actions by monitoring, detecting and preventing the processing of sensitive data without meeting the desired conditions. Blocking can be done during use (in-use, terminal operations), in motion (in-transit, network traffic) or in storage locations (at-rest).