Advanced Research in Data Privacy (Studies in Computational

This booklet offers an outline of the examine paintings on info privateness and privateness bettering applied sciences carried by way of the members of the ARES undertaking. ARES (Advanced examine in privateness an defense, CSD2007-00004) has been some of the most very important study initiatives funded by way of the Spanish executive within the fields of machine safeguard and privateness. it's a part of the now extinct CONSOLIDER INGENIO 2010 software, a hugely aggressive software which aimed to enhance wisdom and open new examine strains between most sensible Spanish examine teams. The undertaking begun in 2007 and should end this 2014. Composed by means of 6 examine teams from 6 assorted associations, it has amassed a massive variety of researchers in the course of its lifetime.

Among the paintings produced through the ARES undertaking, one particular paintings package deal has been with regards to privateness. This books gathers works produced through individuals of the venture regarding information privateness and privateness bettering applied sciences. The offered works not just summarize very important examine carried within the undertaking but in addition function an summary of the state-of-the-art in present learn on facts privateness and privateness improving applied sciences.

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Extra info for Advanced Research in Data Privacy (Studies in Computational Intelligence, Volume 567)

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An Information Retrieval Approach to Document Sanitization. Chapter 9, Advanced Research on Data Privacy. Springer, Berlin (2014) 48. : On the protection of social networks user’s information. -Based Syst. 49, 134–144 (2013) 49. : Approximating degree sequences with regular graphic sequences, manuscript (2014) 50. : A Summary of k-Degree Anonymous Methods for Privacy-Preserving on Networks. Chapter 13, Advanced Research on Data Privacy. Springer, Berlin (2014) 51. : Data protection for online social networks and p-stability for graphs, manuscript (2014) 52.

See [1, 2] for a detailed description of the classification, and a survey on these areas. See also the following texts and monographies [3–7]. V. org G. cat © Springer International Publishing Switzerland 2015 G. Navarro-Arribas and V. 1007/978-3-319-09885-2_3 27 28 V. Torra and G. Navarro-Arribas In this chapter we present the main results of our group in the field of data privacy organized according to the previous classification about whose privacy is being protected. As it will be seen below, most of our research has been focused towards data-driven methods for privacy protection.

Towards knowledge intensive data privacy. Data privacy management and autonomous spontaneous security. Lect. Notes Comput. Sci. 6514, 1–7 (2011) 74. : Towards semantic microaggregation of categorical data for confidential documents. Lect. Notes Comput. Sci. 6408, 266–276 (2010) 75. , Sanchez, D. Semantic anonymisation of categorical datasets. Chapter 7, Advanced Research on Data Privacy. Springer, Berlin (2014) Part II Respondent Privacy: SDC and PPDM A Review of Attribute Disclosure Control Stan Matwin, Jordi Nin, Morvarid Sehatkar and Tomasz Szapiro Abstract Attribute disclosure occurs when the adversary can infer some sensitive information about an individual without identifying individual’s record in the published data set.

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