Document sanitization: measuring search engine information loss and risk of disclosure for the wikileaks cables

Authors:
David F. Nettleton;Daniel Abril
Affiliations:
IIIA-CSIC Artificial Intelligence Research Institute, Spanish National Research Council, Spain,Universitat Pompeu Fabra, Spain;IIIA-CSIC Artificial Intelligence Research Institute, Spanish National Research Council, Spain,Universitat Autonòma de Barcelona, Spain
Venue:
PSD'12 Proceedings of the 2012 international conference on Privacy in Statistical Databases
Year:
2012

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Abstract

In this paper we evaluate the effect of a document sanitization process on a set of information retrieval metrics, in order to measure information loss and risk of disclosure. As an example document set, we use a subset of the Wikileaks Cables, made up of documents relating to five key news items which were revealed by the cables. In order to sanitize the documents we have developed a semi-automatic anonymization process following the guidelines of Executive Order 13526 (2009) of the US Administration, by (i) identifying and anonymizing specific person names and data, and (ii) concept generalization based on WordNet categories, in order to identify words categorized as classified. Finally, we manually revise the text from a contextual point of view to eliminate complete sentences, paragraphs and sections, where necessary. We show that a significant sanitization can be applied, while maintaining the relevance of the documents to the queries corresponding to the five key news items.