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[1] Data anonymization may enable the transfer of information across a boundary, such as between two departments within an agency or between two agencies, while reducing the risk of unintended disclosure, and in certain environments in a manner that enables evaluation and analytics post-anonymization.
Once an individual's privacy has been breached as a result of re-identification, future breaches become much easier: once a link is made between one piece of data and a person's real identity, any association between the data and an anonymous identity breaks the anonymity of the person. [3]
Internet privacy involves the right or mandate of personal privacy concerning the storage, re-purposing, provision to third parties, and display of information pertaining to oneself via the Internet. [1] [2] Internet privacy is a subset of data privacy [3].
This hides the edit from the view of all but other administrators. Many privacy breaches can be addressed sufficiently with simple deletion. Deletion is appropriate for certain personal attacks and may be an appropriate step in removing a serious privacy breach from the database before an editor with oversight privileges can be reached.
The word privacy is derived from the Latin word and concept of ‘privatus’, which referred to things set apart from what is public; personal and belonging to oneself, and not to the state. [3]
Access to personal data: Here, a user gains control over the privacy of their data within a service because the service provider's infrastructure allows users to inspect, correct or delete all their data that is stored at the service provider. Enhanced privacy ID (EPID) is a digital signature algorithm supporting anonymity.
Information privacy is the relationship between the collection and dissemination of data, technology, the public expectation of privacy, contextual information norms, and the legal and political issues surrounding them. [1] It is also known as data privacy [2] [3] or data protection.
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 some privacy.