Anonymizing Unstructured Data

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In this paper we consider the problem of anonymizing datasets in which each individual is associated with a set of items that constitute private information about the individual. Illustrative datasets include market-basket datasets and search engine query logs. We formalize the notion of k-anonymity for set-valued data as a variant of the k-anonymity model for traditional relational datasets. We define an optimization problem that arises from this definition of anonymity and provide O(klogk) and O(1)-approximation algorithms for the same. We demonstrate applicability of our algorithms to the America Online query log dataset.
9 pages, 1 figure

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Databases, Data Structures and Algorithms

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http://salesiana.dossiersoluciones.com/handle/123456789/172902

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0810.5582
 http://arxiv.org/abs/0810.5582

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arXiv