What is one goal of data classification in software security?

The goal of data classification in software security primarily revolves around applying appropriate security measures based on the sensitivity of the data. By categorizing data into different classes, such as public, confidential, or classified, organizations can determine the level of access control, encryption, and other protective measures that need to be implemented to safeguard the data.

This process is critical for ensuring that sensitive information is adequately protected against unauthorized access and potential breaches, while also ensuring that less sensitive data is not overprotected, which could lead to unnecessary expenses and inefficiencies. Effective data classification enables organizations to prioritize security resources and comply with regulatory requirements, ultimately fostering a more secure software environment.

The other choices, while they may relate to data management in some capacity, do not directly address the security aspect that data classification aims to achieve. Developing new data structures focuses on the organization or storage of data rather than its security considerations. Reducing storage costs and improving data retrieval times are both operational goals that can be influenced by data management strategies but are not specific to the principles of data classification within a security context.