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Data anonymization
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!!! Overview
[{$pagename}] or [Pseudonymization] is a type of [privacy Enhancing Technologies]
[{$pagename}] is a procedure by which the most [attributes] within a [data] record are replaced by one or more artificial identifiers, or [pseudonyms].
There can be a single [pseudonym] for a collection of replaced fields or a [pseudonym] per replaced field. The purpose is to render the [data] record less [identifying|Identification] and therefore lower [End-User] or [patient] objections to its use.
[{$pagename}] is the process of either [encrypting|Encryption] or removing [personally Identifiable Information] from [data] sets, so that the [Personal Entity] whom can remain [anonymous].
The Privacy Technology Focus Group defines [{$pagename}] as "technology that converts [clear text|message] data into a [non-person entity] readable and irreversible form, [hashing] and [encryption] techniques in which the decryption key has been discarded."
[{$pagename}] enables the [Data In Transit] across a boundary, such as between two departments within an agency or between two agencies, while reducing the risk of unintended [Disclosure], and in certain environments in a manner that enables evaluation and [analytics] post-anonymization.
!! [Health Data Set|Health Dataset]
[{$pagename}] in the [context] of [medical data|HIPAA], anonymized [data] refers to [Patient Data] from which the [patient] cannot be identified by the recipient of the information. [HIPAA] is very specific on what [data] [MUST] be removed together with any other information which, in conjunction with other [data] held by or disclosed to the recipient, could provide [Identification] the [patient].
Following [{$pagename}] on [Protected Health Information], the [data] is no longer [Protected Health Information] and is referred to a [Health Dataset]
[De-anonymization] is the reverse process in which [anonymous] data is cross-referenced with other data sources to re-identify the [anonymous] data source.
Generalization and perturbation are the two popular anonymization approaches for relational data.
!! [vulnerability] of [{$pagename}][2][3]
[{$pagename}] ability to maintain [anonymity] within [{$pagename}] data sets is questionable. Several reports indicate that a small amount of externally associated data may provide [De-anonymization]
!! More Information
There might be more information for this subject on one of the following:
[{ReferringPagesPlugin before='*' after='\n' }]
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* [#1] - [Data_anonymization|Wikipedia:Data_anonymization|target='_blank'] - based on information obtained 2016-07-06
* [#2] - [No silver bullet: De-identification still doesn’t work|https://freedom-to-tinker.com/blog/randomwalker/no-silver-bullet-de-identification-still-doesnt-work/|target='_blank'] - based on information obtained 2016-08-14
* [#3] - [SCIENTISTS EXPOSE NEW VULNERABILITIES IN THE SECURITY OF PERSONAL GENETIC INFORMATION|http://wi.mit.edu/news/archive/2013/scientists-expose-new-vulnerabilities-security-personal-genetic-information|target='_blank'] - based on information obtained 2016-08-14
This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthorTop