Pseudonymisation & Anonymisation as Tools for Managing Data Protection Risk

Pseudonymisation and anonymisation are two of the most frequent techniques used in modern data protection and privacy management. Yet, we find that organisations sometimes apply both concepts incorrectly. In this update, we explain the key differences, practical applications, and why understanding these concepts is critical for compliance with data protection laws.

Understanding Pseudonymisation under the Nigeria Data Protection Act.

Pseudonymisation involves processing personal data so that it cannot be directly attributed to a specific individual without additional information. Typically, this means replacing identifiers, like names, phone numbers, or email addresses, with a code, token, or other pseudonym.

For example, in a database of customer records, "John" Smith ight become "cu_7ys_". The original data can only be restored if a secure mapping table or key is available. The main benefits of pseudonymisation include:

1. Reduced risk in case of data breaches: Even if attackers gain access to the pseudonymised dataset, they cannot easily link the information back to individuals without the separate key.

2. Regulatory compliance: Laws like the NDPA encourage pseudonymisation as a privacy-enhancing technique, demonstrating that organisations take reasonable steps to protect personal data.

3. Operational utility: Pseudonymised data can still be used for analytics, research, and internal reporting while limiting exposure of sensitive identifiers.

However, pseudonymised data remains personal data under the law because it can potentially be re-identified. Under the NDPA, organisations must still implement strict access controls, encryption, and audit procedures to maintain compliance.

Understanding Anonymisation under the Nigeria Data Protection Act.

Anonymisation, in contrast, is the process of irreversibly removing or altering personal identifiers so that individuals cannot be identified by any means. Unlike pseudonymisation, anonymised data is considered no longer personal data under laws like NDPA. A practical example would be removing names, phone numbers, and email addresses from a dataset and aggregating information so that it’s impossible to link a record back to a specific individual. Anonymisation will be a great compliance strategy where the objective is to share fully anonymised datasets with researchers, partners, or the public without exposing individual privacy. The key limitation is that anonymisation can reduce the utility of Personal Data. Once identifiers are removed irreversibly, certain operations like personalised outreach or detailed auditing become impossible.

Key Considerations

1. For organisations looking to demonstrate accountability, reduce risk, and build trust with customers, employees, and regulators alike, pseudonymising or anonymising sensitive information is a prudent compliance strategy.

2. Confusing pseudonymisation with anonymisation or applying them incorrectly, can have serious consequences, including regulatory fines under NDPA and other data protection laws.