SEC07-BP02 Apply data protection controls based on data sensitivity - Security Pillar

SEC07-BP02 Apply data protection controls based on data sensitivity

Apply data protection controls that provide an appropriate level of control for each class of data defined in your classification policy.  This practice can allow you to protect sensitive data from unauthorized access and use, while preserving the availability and use of data.

Desired outcome: You have a classification policy that defines the different levels of sensitivity for data in your organization.  For each of these sensitivity levels, you have clear guidelines published for approved storage and handling services and locations, and their required configuration.  You implement the controls for each level according to the level of protection required and their associated costs.  You have monitoring and alerting in place to detect if data is present in unauthorized locations, processed in unauthorized environments, accessed by unauthorized actors, or the configuration of related services becomes non-compliant.

Common anti-patterns:

  • Applying the same level of protection controls across all data. This may lead to over-provisioning security controls for low-sensitivity data, or insufficient protection of highly sensitive data.

  • Not involving relevant stakeholders from security, compliance, and business teams when defining data protection controls.

  • Overlooking the operational overhead and costs associated with implementing and maintaining data protection controls.

  • Not conducting periodic data protection control reviews to maintain alignment with classification policies.

Benefits of establishing this best practice: By aligning your controls to the classification level of your data, your organization can invest in higher levels of control where needed. This can include increasing resources on securing, monitoring, measuring, remediating, and reporting.  Where fewer controls are appropriate, you can improve the accessibility and completeness of data for your workforce, customers, or constituents.  This approach gives your organization the most flexibility with data usage, while still adhering to data protection requirements.

Level of risk exposed if this best practice is not established: High

Implementation guidance

Implementing data protection controls based on data sensitivity levels involves several key steps. First, identify the different data sensitivity levels within your workload architecture (such as public, internal, confidential, and restricted) and evaluate where you store and process this data. Next, define isolation boundaries around data based on its sensitivity level. We recommend you separate data into different AWS accounts, using service control policies (SCPs) to restrict services and actions allowed for each data sensitivity level. This way, you can create strong isolation boundaries and enforce the principle of least privilege.

After you define the isolation boundaries, implement appropriate protection controls based on the data sensitivity levels. Refer to best practices for Protecting data at rest and Protecting data in transit to implement relevant controls like encryption, access controls, and auditing. Consider techniques like tokenization or anonymization to reduce the sensitivity level of your data. Simplify applying consistent data policies across your business with a centralized system for tokenization and de-tokenization.

Continuously monitor and test the effectiveness of the implemented controls. Regularly review and update the data classification scheme, risk assessments, and protection controls as your organization's data landscape and threats evolve. Align the implemented data protection controls with relevant industry regulations, standards, and legal requirements. Further, provide security awareness and training to help employees understand the data classification scheme and their responsibilities in handling and protecting sensitive data.

Implementation steps

  1. Identify the classification and sensitivity levels of data within your workload.

  2. Define isolation boundaries for each level and determine an enforcement strategy.

  3. Evaluate the controls you define that govern access, encryption, auditing, retention, and others required by your data classification policy.

  4. Evaluate options to reduce the sensitivity level of data where appropriate, such as using tokenization or anonymization.

  5. Verify your controls using automated testing and monitoring of your configured resources.

Resources

Related best practices:

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