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De-anonymization is the reverse process in which anonymous data is cross-referenced with other data sources to re-identify the anonymous data source. [3] Generalization and perturbation are the two popular anonymization approaches for relational data. [ 4 ]
[11] [12] [13] The data was released by Netflix 2006 after de-identification, which consisted of replacing individual names with random numbers and moving around personal details. The two researchers de-anonymized some of the data by comparing it with non-anonymous IMDb (Internet Movie Database) users' movie ratings.
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As the queries were attributed by AOL to particular user numerically identified accounts, an individual could be identified and matched to their account and search history. [1] 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 ]
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The call is bridged or transferred and arrives with the spoofed number chosen by the caller—thus tricking the called party. Many providers also provide a Web-based interface or a mobile application where a user creates an account, logs in and supplies a source number, destination number, and the bogus caller ID information to be displayed.
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