identifierbarhet

Identifierbarhet refers to the quality of information that allows an individual to be identified. In data protection contexts, identifiability describes how easily a dataset or data element can be linked to a specific person, either directly through identifiers such as a name or personal number, or indirectly through combinations of attributes that, together with external information, reveal an identity.

Identifiability depends on the amount of detail in the data, the presence of quasi-identifiers, and the availability of supplementary datasets. Even data from which direct identifiers have been removed can remain identifiable if an attacker can combine the remaining attributes with external data sources or background knowledge.

In regulatory and ethical contexts, identifiability is a central privacy concern. If data are identifiable, they are typically treated as personal data, subject to privacy protections. Measures to reduce identifiability aim to protect privacy while preserving some data utility. Common methods include anonymization or pseudonymization, data minimization, data aggregation, and controlled access. Technical approaches such as k-anonymity, l-diversity, and differential privacy seek to limit the risk of re-identification.

Privacy risk assessments evaluate identifiability by considering the probability of re-identification and the potential consequences for individuals. There is often a trade-off between data usefulness and privacy protection: stronger protections reduce identifiability but can limit data utility, while higher identifiability increases privacy risk.

Limitations include evolving external data sources and advances in re-identification techniques. Ongoing governance, monitoring, and risk management are important to maintain appropriate levels of identifiability over time.