Overview#

Data anonymization is a type of privacy Enhancing Technologies

Data anonymization is the process of either encrypting or removing personally Identifiable Information from personal data sets, so that the Personal Entity whom can remain anonymous.

The Privacy Technology Focus Group defines Data anonymization as "technology that converts clear text data into a non-person entity readable and irreversible form, hashing and encryption techniques in which the decryption key has been discarded."

Data anonymization enables the Data In Transit across a boundary, such as between two departments within an agency or between two agencies, while reducing the risk of unintended disclosure, and in certain environments in a manner that enables evaluation and analytics post-anonymization.

Health Data Set#

Data anonymization in the context of medical data, anonymized data refers to Patient Data from which the patient cannot be identified by the recipient of the information. The name, address, and full post code must be removed together with any other information which, in conjunction with other data held by or disclosed to the recipient, could identify the patient.

Following Data anonymization on Protected Health Information, the data is no longer Protected Health Information and is referred to a Health Data Set

De-anonymization is the reverse process in which anonymous data is cross-referenced with other data sources to re-identify the anonymous data source.

Generalization and perturbation are the two popular anonymization approaches for relational data.

vulnerability of Data anonymization[2][3]#

Data anonymization ability to maintain anonymity within Data anonymization data sets is questionable. Several reports indicate that a small amount of externally associated data may provide De-anonymization

More Information#

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« This page (revision-9) was last changed on 14-Aug-2016 12:15 by jim