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Anonymizing Binary Tables is APX-hard (2007)

Abstract
The problem of publishing personal data without giving up privacy is increasingly important. An interesting formalization is the $k$-anonymization, where all rows in a table are clustered in sets of at least $k$ records, and all the entries for which records in the same cluster have different values are suppressed. The problem has been shown to be NP-hard when the records values are over a ternary alphabet and $k=3$. In this paper we show that the problem is not only NP-hard, but also APX-hard, when the records values are over a binary alphabet and $k=3$.

Publication details
Download http://arxiv.org/abs/0707.0421
Repository arXiv (United States)
Keywords Computer Science - Databases, Computer Science - Computational Complexity, Computer Science - Data Structures and Algorithms
Type text