privacy

Towards a private vector space model for confidential documents

Publication Type:

Conference Paper

Source:

Symposium On Applied Computing, ACM, Coimbra, Portugal, p.944--945 (2013)

ISBN:

978-1-4503-1656-9

URL:

http://doi.acm.org/10.1145/2480362.2480543

Keywords:

anonymization; document vector space; indexes; privacy

Abstract:

We introduce in this paper a method to anonymize document vector spaces. These vector spaces can be used to analyze confidential documents without disclosing private information. The method is inspired in microaggregation, a popular technique used in statistical disclosure control.

Privacy in Data Mining

Publication Type:

Book Chapter

Authors:

Vicenç Torra

Source:

Data Mining and Knowledge Discovery Handbook, Springer, p.687-716 (2010)

Semantic Microaggregation for the Anonymization of Query Logs

Publication Type:

Conference Paper

Source:

PSD 2010, Springer, Volume 6344, Greece, p.127-137 (2010)

Using Classification Methods to Evaluate Attribute Disclosure Risks

Publication Type:

Conference Paper

Source:

MDAI 2010, Springer, Volume 6408, France, p.277-286 (2010)

Distributed Privacy-Preserving Methods for Statistical Disclosure Control

Publication Type:

Conference Paper

Source:

Int. Workshop on Data Privacy Management (DPM'09), Springer, Volume 5939, France, p.33-47 (2010)

Classifying data from protected statistical datasets

Publication Type:

Journal Article

Source:

Computer and Security, Volume 29, Issue 8, p.875-890 (2010)

Information loss for synthetic data through fuzzy clustering

Publication Type:

Journal Article

Source:

Int. J. of Uncertainty, Fuzziness and Knowledge-Based Systems, World Scientific , Volume 18, Issue 1, p.25-37 (2010)

Privacy-preserving data-mining through micro-aggregation for web-based e-commerce

Publication Type:

Journal Article

Source:

Internet Research, Emerald Group Publishing Limited, Volume 20, Issue 3, p.366-384 (2010)

URL:

http://dx.doi.org/10.1108/10662241011050759

Towards Semantic Microaggregation of Categorical Data for Confidential Documents

Publication Type:

Conference Proceedings

Source:

Modeling Decisions for Artificial Intelligence, MDAI 2010, Springer, Volume 6408, Perpignan, France, p.266-276 (2010)

URL:

http://www.springerlink.com/content/f41402862155w6t4/

Keywords:

Web indexing task; classification task; frequency term vector; k-anonymity preservation; privacy preserving information retrieval; semantic microaggregation; Internet; data privacy; information retrieval; pattern classification; vectors

Abstract:

In the data privacy context, specifically, in statistical disclosure control techniques, microaggregation is a well-known microdata protection method, ensuring the confidentiality of each individual. In this paper, we propose a new approach of microaggregation to deal with semantic sets of categorical data, like text documents. This method relies on the WordNet framework that provides complete semantic relationship taxonomy between words. Therefore, this extension aims ensure the confidentiality of text documents, but at the same time, it should preserve the general meaning. We apply some measures to evaluate the quality of the protection method relying on information loss.

Generation of Synthetic Data by means of Fuzzy c-Regression

Publication Type:

Conference Paper

Source:

2009 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2009, IEEE, Jeju Island, Korea, p.1145-1150 (2009)

ISBN:

978-1-4244-3597-5

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