By Guillermo Navarro-Arribas, Vicenç Torra
This booklet offers an summary of the learn paintings on information privateness and privateness improving applied sciences carried by means of the members of the ARES undertaking. ARES (Advanced examine in privateness an safeguard, CSD2007-00004) has been the most very important learn tasks funded by way of the Spanish executive within the fields of computing device defense and privateness. it really is a part of the now extinct CONSOLIDER INGENIO 2010 software, a hugely aggressive software which aimed to enhance wisdom and open new study traces between best Spanish examine teams. The undertaking begun in 2007 and should end this 2014. Composed by means of 6 study teams from 6 assorted associations, it has accrued a big 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 with regards to privateness. This books gathers works produced by way of participants of the venture regarding facts privateness and privateness bettering applied sciences. The provided works not just summarize very important learn carried within the undertaking but additionally function an summary of the state-of-the-art in present study on facts privateness and privateness improving technologies.
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Additional info for Advanced Research in Data Privacy
3 we describe our results on userprivacy. In Sect. 4 we briefly discuss the topic of knowledge-intensive data privacy. The chapter finishes with a summary. 2 Research on Data-Driven or General-Purpose Protection Methods In the last years we have taken into account the three main issues related to data-driven methods: • data protection methods, the methods that are needed to protect the data • information loss measures, to evaluate in what extent a released data set can compromise privacy. • disclosure risk.
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. AOL Search Data Scandal. org/wiki/AOL_search_data_leak. Accessed Aug 2006 43. ODP. Open directory project. org/ 44. The Tor Project Inc: Tor: Overview.
En Data Privacy: A Survey of Results Vicenç Torra and Guillermo Navarro-Arribas Abstract In this paper we present an overview of the results obtained by our research group within the area of data privacy. Results focus on data-driven problems (respondent and owner privacy with an unknown use) and user privacy. We have developed some new masking methods, developed methodologies for parameter selection, and developed some information loss and disclosure risk measures. We have also obtained important results on reidentification methods (record linkage) when used for disclosure risk assessment.