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Definition
m-invariance is a technique for protecting privacy when publishing the snapshots of dynamic datasets that contain sensitive personal information.
Theory
Organizations like census bureaus and hospitals maintain large datasets (referred to as microdata) that contain personal information (e.g., census data and medical records). Such data collections are of significant research value, and there is much benefit in making them publicly available. Nevertheless, as the data is sensitive in nature, proper measures must be taken to ensure that its publication does not endanger the privacy of the individuals that contributed the data. A canonical solution to this problem is to modify the data before releasing it to the public, such that the modification prevents inference of private information while retaining statistical characteristics of the data.
For example, suppose that a hospital wants to release...
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Samarati P (2001) Protecting respondents’ identities in microdata release. IEEE Trans Knowl Data Eng 13(6):1010–1027
Machanavajjhala A, Kifer D, Gehrke J, Venkitasubramaniam M (2007) L-diversity: privacy beyond k-anonymity. TKDDÂ 1(1)
Xiao X, Tao Y (2007) M-invariance: towards privacy preserving re-publication of dynamic datasets. In: SIGMOD conference, Beijing, China, pp 689–700
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© 2011 Springer Science+Business Media, LLC
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Xiao, X. (2011). M-Invariance. 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_901
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DOI: https://doi.org/10.1007/978-1-4419-5906-5_901
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-5905-8
Online ISBN: 978-1-4419-5906-5
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