Aligning Data Classification Standards with Best Practices

C.

When developing data classification standards, it is important to ensure that they align with best practices. Internal audit can provide valuable advice in this area. In order to determine the best approach, internal audit should consider a variety of factors, including the organization's risk assessment, business requirements, segregation of duties requirements, and authentication requirements.

Option A suggests that the standards should be based on the results of an organization-wide risk assessment. This is a recommended approach to data classification as it ensures that the classification is based on the risk of harm that could result from the unauthorized disclosure, modification or destruction of the information. This approach is aligned with best practices because it helps the organization to identify and prioritize the protection of its most sensitive and valuable data. By classifying data based on the results of a risk assessment, the organization can apply appropriate controls to protect it, such as access controls, encryption, and backup and recovery procedures.

Option B suggests that the standards should be based on the business requirements for confidentiality of the information. While business requirements are an important consideration when developing data classification standards, they may not necessarily align with best practices. Confidentiality is just one aspect of data protection, and other factors, such as integrity and availability, should also be considered.

Option C suggests that the standards should be aligned with the organization's segregation of duties requirements. While segregation of duties is an important control for preventing fraud and errors, it may not be directly related to data classification. Data classification is primarily concerned with the protection of information based on its sensitivity, whereas segregation of duties is concerned with preventing a single individual from having too much control over a process.

Option D suggests that the standards should be based on the business requirements for authentication of the information. While authentication is an important control for ensuring the confidentiality, integrity, and availability of data, it is not directly related to data classification. Authentication refers to the process of verifying the identity of a user or system, whereas data classification is concerned with the sensitivity of the information itself.

Therefore, the most appropriate recommendation would be option A, based on the results of an organization-wide risk assessment. This aligns with best practices and ensures that the classification of data is based on the risk of harm that could result from the unauthorized disclosure, modification or destruction of the information.