Search results
Results from the WOW.Com Content Network
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 ...
The following example demonstrates a failing with k-anonymity: there may exist other data records that can be linked on the variables that are allegedly non-identifying. For instance, suppose an attacker is able to obtain the log from the person who was taking vital signs as part of the study and learns that Kishor was at the hospital on April ...
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 ...
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 ...
Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Help; Learn to edit; Community portal; Recent changes; Upload file
The New York Times was able to locate an individual from the released and anonymized search records by cross referencing them with phonebook listings. [2] Consequently, the ethical implications of using this data for research are under debate. [3] [4] AOL acknowledged it was a mistake and removed the data; however, the removal was too late.