Quasi-identifier

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Quasi-identifiers are pieces of information that are not of themselves unique identifiers, but are sufficiently well correlated with an entity that they can be combined with other quasi-identifiers to create a unique identifier.^[1]

Quasi-identifiers can thus, when combined, become personally identifying information. This process is called re-identification. As an example, Latanya Sweeney has shown that even though neither gender, birth dates nor postal codes uniquely identify an individual, the combination of all three is sufficient to identify 87% of individuals in the United States.^[2]

The term was introduced by Tore Dalenius in 1986. ^[3] Since then, quasi-identifiers have been the basis of several attacks on released data. For instance, Sweeney linked health records to publicly available information to locate the then-governor of Massachusetts‘ hospital records using uniquely-identifying quasi-identifiers, ^{[4] [5]} and Sweeney, Abu and Winn used public voter records to re-identify participants in the Personal Genome Project. ^[6] Additionally, Arvind Narayanan and Vitaly Shmatikov made use of quasi-identifiers to de-anonymize data released by Netflix. ^[7]

Motwani and Ying warn about potential privacy breaches being enabled by publication of large volumes of government and business data containing quasi-identifiers. ^[8]