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k-Anonymity

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Related Concepts

Identity Disclosure; Microdata Protection

Definition

k-Anonymity is a property that captures the protection of released data against possible reidentification of the respondents to whom the data refer. k-Anonymity states that the released data should be indistinguishably related to no less than k respondents.

Background

The increased power and interconnectivity of computer systems available today provide the ability of storing, processing, sharing, and disseminating large amounts of data, resulting in networked information accessible anywhere anytime. If in the past the released information was mostly in statistical and tabular form (macrodata), many situations require today that the specific stored data themselves (microdata) be released. The advantage of releasing microdata instead of specific precomputed statistics is an increased flexibility and availability of information for the users. To protect the anonymity of the entities, called respondents, to whom the...

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Recommended Reading

  1. Bayardo RJ, Agrawal R (2005) Data privacy through optimal k-anonymization. In: Proceedings of the International Conference on Data Engineering (ICDE’05), Tokyo, Japan, April 2005

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  2. Ciriani V, De Capitani di Vimercati S, Foresti S, Samarati P (2007) k-Anonymity. In: Yu T, Jajodia S (eds) Security in Decentralized Data Management. Springer, Heidelberg

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  3. LeFevre K, DeWitt D, Ramakrishnan R (2006) Mondrian multidimensional k-anonymity. In: Proceedings of the International Conference on Data Engineering (ICDE’06), Atlanta, GA, April 2006

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  4. Samarati P (2001) Protecting respondents’ identities in microdata release. IEEE Trans Knowl Data Eng 13(6):1010–1027

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© 2011 Springer Science+Business Media, LLC

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Samarati, P. (2011). k-Anonymity. In: van Tilborg, H.C.A., Jajodia, S. (eds) Encyclopedia of Cryptography and Security. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-5906-5_754

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