The k-Anonymity Problem Is Hard
The problem of publishing personal data without giving up privacy is becoming increasingly important. An interesting formalization recently proposed is the k-anonymity. This approach requires that the rows in a table are clustered in sets of size at least k and that all the rows in a cluster are related to the same tuple, after the suppression of some records. The problem has been shown to be NP-hard when the values are over a ternary alphabet, k = 3 and the rows length is unbounded. In this paper we give a lower bound on the approximation of two restrictions of the problem, when the records values are over a binary alphabet and k = 3, and when the records have length at most 8 and k = 4, showing that these restrictions of the problem are APX-hard.
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- 5.Park, H., Shim, K.: Approximate algorithms for k-Anonymity. In: Chan, C.Y., Ooi, B.C., Zhou, A. (eds.) ACM SIGMOD International Conference on Management of Data, pp. 67–78. ACM Press, New York (2007)Google Scholar