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For example, given prior knowledge of a few attendance dates it is easy to identify someone's data in a pseudonymized dataset by selecting only those people with that pattern of dates. This is an example of an inference attack. The weakness of pre-GDPR pseudonymized data to inference attacks is commonly overlooked.
De-identification is the process used to prevent someone's personal identity from being revealed. For example, data produced during human subject research might be de-identified to preserve the privacy of research participants. Biological data may be de-identified in order to comply with HIPAA regulations that define and stipulate patient ...
Data re-identification or de-anonymization is the practice of matching anonymous data (also known as de-identified data) with publicly available information, or auxiliary data, in order to discover the person to whom the data belongs. [1]
A pseudonym (/ ˈ sj uː d ə n ɪ m /; from Ancient Greek ψευδώνυμος (pseudṓnumos) 'lit. falsely named') or alias (/ ˈ eɪ l i. ə s /) is a fictitious name that a person assumes for a particular purpose, which differs from their original or true meaning ().
Additionally, Arvind Narayanan and Vitaly Shmatikov discussed on quasi-identifiers to indicate statistical conditions for de-anonymizing 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.
For data storage, identification is the capability to find, retrieve, report, change, or delete specific data without ambiguity. This applies especially to information stored in databases. In database normalisation , the process of organizing the fields and tables of a relational database to minimize redundancy and dependency, is the central ...
An important factor is that the processing must be irreversible. The Directive does not clarify how such a de-identification process should or could be performed. The focus is on the outcome: that data should be such as not to allow the data subject to be identified via “all” “likely” and “reasonable” means.
The PCI Council recommends independent vetting and validation of any claims of security and compliance: "Merchants considering the use of tokenization should perform a thorough evaluation and risk analysis to identify and document the unique characteristics of their particular implementation, including all interactions with payment card data ...