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According to the EDPS and AEPD, no one, including the data controller, should be able to re-identify data subjects in a properly anonymized dataset. [8] Research by data scientists at Imperial College in London and UCLouvain in Belgium, [9] as well as a ruling by Judge Michal Agmon-Gonen of the Tel Aviv District Court, [10] highlight the ...
The two researchers de-anonymized some of the data by comparing it with non-anonymous IMDb (Internet Movie Database) users' movie ratings. Very little information from the database, it was found, was needed to identify the subscriber. [3] In the resulting research paper, there were startling revelations of how easy it is to re-identify Netflix ...
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 privacy laws. [1] When applied to metadata or general data about identification, the process is also ...
k-anonymity is a property possessed by certain anonymized data.The term k-anonymity was first introduced by Pierangela Samarati and Latanya Sweeney in a paper published in 1998, [1] although the concept dates to a 1986 paper by Tore Dalenius.
l-diversity, also written as ℓ-diversity, is a form of group based anonymization that is used to preserve privacy in data sets by reducing the granularity of a data representation. This reduction is a trade off that results in some loss of effectiveness of data management or mining algorithms in order to gain
Non-Personal Data (NPD) is electronic data that does not contain any information that can be used to identify a natural person.Thus, it can either be data that has no personal information to begin with (such as weather data, stock prices, data from anonymous IoT sensors); or it is data that had personal data that was subsequently pseudoanonymized (for example, identifiable strings substituted ...
An example of application of pseudonymization procedure is creation of datasets for de-identification research by replacing identifying words with words from the same category (e.g. replacing a name with a random name from the names dictionary), [11] [12] [13] however, in this case it is in general not possible to track data back to its origins.
Research on personality commonly employ different data source so as to represent better the pattern of one's distinctive features. [2] [3] L-data, refer to the life-outcome data, such as age, education, income, [4]: 481 student grades at school, criminal and conviction record [5]: 13