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Pseudonymization is a data management and de-identification procedure by which personally identifiable information fields within a data record are replaced by one or more artificial identifiers, or pseudonyms. [1]
Such data has proved to be very valuable for researchers, particularly in health care. GDPR-compliant pseudonymization seeks to reduce the risk of re-identification through the use of separately kept "additional information". The approach is based on an expert evaluation of a dataset to designate some identifiers as "direct" and some as "indirect."
The Complete Book of Data Anonymization: From Planning to Implementation. CRC Press. ISBN 9781482218565. Khaled El Emam, Luk Arbuckle (August 2014). Anonymizing Health Data: Case Studies and Methods to Get You Started. O'Reilly Media. ISBN 978-1-4493-6307-9. Rolf H. Weber, Ulrike I. Heinrich (2012). Anonymization: SpringerBriefs in ...
A unit of Harvard University's Law Library says it is releasing an archive of more than 300,000 government data sets, aiming to protect vital public information at a time when President Donald ...
Pseudonymization is a data management technique that replaces an individual's identity or personal information with an artificial identifiers known as Pseudonyms. This de-identification method enables contents and fields of information to be covered up so as to deter attacks and hackers from obtaining important information.
Dec 25, 2024; Pittsburgh, Pennsylvania, USA; Pittsburgh Steelers linebacker T.J. Watt (90) takes the field against the Kansas City Chiefs at Acrisure Stadium.
Rebounding tech stocks drove U.S. indexes higher Tuesday, a day after they tumbled on doubts about whether the artificial-intelligence frenzy really needs all the dollars being poured into it.
De-identification is adopted as one of the main approaches toward data privacy protection. [7] It is commonly used in fields of communications, multimedia, biometrics, big data, cloud computing, data mining, internet, social networks, and audio–video surveillance. [8]