A.8.11 Data masking
- Andy Systems
- ISMS Guides
A.8.11 Data Masking would include:
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Data Masking Policy: Documentation of a formal data masking policy that outlines the organization's approach to protecting sensitive data through data masking techniques.
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Data Masking Procedures: Detailed procedures and guidelines on how data masking is applied to sensitive data, ensuring that original data is replaced with realistic but fictitious data in non-production environments.
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Data Masking Tools and Technologies: Documentation of the data masking tools and technologies used by the organization to implement data masking, including information about their configuration and integration with relevant systems.
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Data Masking Implementation: Evidence of the successful implementation of data masking techniques on databases, applications, and other data storage systems where sensitive information is stored.
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Data Masking Testing and Validation: Records of testing and validation processes to ensure that data masking is effective and that the masked data retains its integrity and usability for testing and development purposes.
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Access Controls: Evidence of access controls and permissions granted to users who have access to masked data in non-production environments, ensuring that only authorized individuals can view or manipulate this data.
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Compliance Documentation: Evidence of compliance with data protection regulations and industry standards related to data masking and data privacy.
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Data Masking Impact Assessment: Documentation of any assessments conducted to evaluate the impact of data masking on application functionality, performance, and usability.
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Training and Awareness: Evidence of training and awareness programs for employees involved in data masking processes, ensuring they understand the importance of data protection and the proper handling of masked data.
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Data Masking Audit Logs: Logs or records of data masking activities, changes, and access, as well as any incidents or anomalies related to masked data.
These pieces of evidence to assess the adequacy and effectiveness of the organization's data masking controls, ensuring that sensitive data is properly protected from unauthorized access and that the data masking techniques do not negatively impact the organization's operations or compliance efforts.
Data masking is a technique used to protect sensitive data – usually any data that could be deemed personally identifiable information (PII) – over and above an organisation’s standard information security protocols such as access control etc. Data masking, also known as data obfuscation, hides the actual data using modified content like characters or numbers. The main objective of data masking is creating an alternate version of data that cannot be easily identifiable or reverse engineered, protecting data classified as sensitive.
Where the protection of sensitive data (e.g. PII) is a concern, the organization should consider hiding such data by using techniques such as data masking, pseudonymization or anonymization. Pseudonymization or anonymization techniques can hide PII, disguise the true identity of PII principals or other sensitive information, and disconnect the link between PII and the identity of the PII principal or the link between other sensitive information. When using pseudonymization or anonymization techniques, it should be verified that data has been adequately pseudonymized or anonymized.
Additional techniques for data masking include: encryption (requiring authorized users to have a key); nulling or deleting characters (preventing unauthorized users from seeing full messages); varying numbers and dates; substitution (changing one value for another to hide sensitive data); replacing values with their hash.
The following should be considered when implementing and using data masking, pseudonymization or anonymization techniques:
· level of strength of data masking, pseudonymization or anonymization according to the usage of the processed data;
· access controls to the processed data;
· agreements or restrictions on usage of the processed data;
· prohibiting collating the processed data with other information in order to identify the PII principal;
· keeping track of providing and receiving the processed data.
· any legal or regulatory requirements (e.g., requiring the masking of payment cards’ information during processing or storage).