By Guillermo Navarro-Arribas, Vicenç Torra

ISBN-10: 3319098845

ISBN-13: 9783319098845

ISBN-10: 3319098853

ISBN-13: 9783319098852

This publication presents an summary of the learn paintings on facts privateness and privateness improving applied sciences carried by way of the contributors of the ARES venture. ARES (Advanced learn in privateness an defense, CSD2007-00004) has been the most very important learn tasks funded via the Spanish executive within the fields of computing device defense and privateness. it's a part of the now extinct CONSOLIDER INGENIO 2010 application, a hugely aggressive application which aimed to strengthen wisdom and open new learn strains between most sensible Spanish learn teams. The undertaking begun in 2007 and may end this 2014. Composed by way of 6 study teams from 6 diversified associations, it has accumulated a massive variety of researchers in the course of its lifetime.

Among the paintings produced by way of the ARES undertaking, one particular paintings package deal has been relating to privateness. This books gathers works produced by means of participants of the undertaking on the topic of information privateness and privateness improving applied sciences. The offered works not just summarize vital examine carried within the undertaking but in addition function an summary of the cutting-edge in present examine on information privateness and privateness improving technologies.

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Example text

This is the case of noise addition. We developed methods based on microaggregation [29] and noise addition [30] constraint-compliant. We also developed a system to automatically select an appropriate masking method when data was represented using XML and edit constraints were expressed using Schematron [31]. This type of problems were initially considered in [32]. Second, we have considered the problem of multiple releases from the same database. In [14] we reviewed the difficulties of publishing several copies of the same data protected using different approaches, and of several tables from the same database (linked tables).

Distance based re-identification for time series. Analysis of distances. Lect. Notes Comput. Sci. 4302, 205–216 (2006) 40. : A similarity measure for sequences of categorical data based on the ordering of common elements. LNAI 5285, 134–145 (2008) 41. : Generation of prototypes for masking sequences of events. In: Proceedings ARES 2009, WAIS Workshop, pp. 947–952 (2009) 42. : On the use of aggregation operators for location privacy. In: Proceedings IFSA-EUSFLAT, pp. 489–494 (2009) 36 V. Torra and G.

59(4), 1568–1577 (2010) 38. : Associating a numerical semigroup to the triangle-free configurations. Adv. Math. Commun. 5(2), 351–371 (2011) 39. : Linear spaces and transversal designs: k-anonymous combinatorial configurations for anonymous database search. Des. Codes Crypt. 71, 503–524 (2014) 40. : On the privacy offered by k-d-anonymity. Inf. Syst. 38(4), 491–494 (2013) 41. : Using social networks to distort users’ profiles generated by web search engines. Comput. Netw. 54(9), 1343–1357 (2010) 42.

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Advanced Research in Data Privacy by Guillermo Navarro-Arribas, Vicenç Torra


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