Abstract
Uncertainty and indistinguishability are two independent aspects of privacy. Uncertainty refers to the property that the attacker cannot tell which private value, among a group of values, an individual actually has, and indistinguishability refers to the property that the attacker cannot see the difference among a group of individuals. While uncertainty has been well studied and applied to many scenarios, to date, the only effort in providing indistinguishability has been the well-known notion of k-anonymity. However, k-anonymity only applies to anonymized tables. This paper defines indistinguishability for general situations based on the symmetry among the possible private values associated with individuals. The paper then discusses computational complexities of and provides practical algorithms for checking whether a set of database views provides enough indistinguishability.
The work was partially supported by the NSF grants IIS-0430402, IIS-0430165, and IIS-0242237.
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Yao, C., Wang, L., Wang, S.X., Jajodia, S. (2006). Indistinguishability: The Other Aspect of Privacy. In: Jonker, W., Petković, M. (eds) Secure Data Management. SDM 2006. Lecture Notes in Computer Science, vol 4165. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11844662_1
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DOI: https://doi.org/10.1007/11844662_1
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