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Increasing polynomial regression complexity for data anonymization
dc.contributor.author | Nin Guerrero, Jordi |
dc.contributor.author | Pont Tuset, Jordi |
dc.contributor.author | Medrano Gracia, Pau |
dc.contributor.author | Larriba Pey, Josep |
dc.contributor.author | Muntés Mulero, Víctor |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions |
dc.date.accessioned | 2011-09-28T10:47:13Z |
dc.date.available | 2011-09-28T10:47:13Z |
dc.date.created | 2007 |
dc.date.issued | 2007 |
dc.identifier.citation | Nin, J. [et al.]. Increasing polynomial regression complexity for data anonymization. A: International Conference on Intelligent Pervasive Computing. "2007 International Conference on Intelligent Pervasive Computing". Jeju Island: IEEE Computer Society, 2007, p. 29-34. |
dc.identifier.isbn | 0-7695-3006-0 |
dc.identifier.uri | http://hdl.handle.net/2117/13376 |
dc.description.abstract | Pervasive computing and the increasing networking needs usually demand from publishing data without revealing sensible information. Among several data protection methods proposed in the literature, those based on linear regression are widely used for numerical data. However, no attempts have been made to study the effect of using more complex polynomial regression methods. In this paper, we present PoROP-k, a family of anonymizing methods able to protect a data set using polynomial regressions. We show that PoROP-k not only reduces the loss of information, but it also obtains a better level of protection compared to previous proposals based on linear regressions. |
dc.format.extent | 6 p. |
dc.language.iso | eng |
dc.publisher | IEEE Computer Society |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Seguretat informàtica |
dc.subject.lcsh | Data protection |
dc.subject.other | Regression analysis |
dc.subject.other | Security of data |
dc.subject.other | Ubiquitous computing |
dc.title | Increasing polynomial regression complexity for data anonymization |
dc.type | Conference report |
dc.subject.lemac | Protecció de dades |
dc.contributor.group | Universitat Politècnica de Catalunya. DAMA-UPC - Data Management Group |
dc.identifier.doi | 10.1109/IPC.2007.103 |
dc.description.peerreviewed | Peer Reviewed |
dc.rights.access | Open Access |
local.identifier.drac | 2440725 |
dc.description.version | Postprint (published version) |
local.citation.author | Nin, J.; Pont, J.; Medrano, P.; Larriba, J.; Muntés, V. |
local.citation.contributor | International Conference on Intelligent Pervasive Computing |
local.citation.pubplace | Jeju Island |
local.citation.publicationName | 2007 International Conference on Intelligent Pervasive Computing |
local.citation.startingPage | 29 |
local.citation.endingPage | 34 |