Data/hora: 12/06/2024 09:20:24

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	18/09/2008	
Data da última atualização: 	16/01/2020	
Autoria: 	OLIVEIRA, S. R. de M.	
Afiliação: 	STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA.	
Título: 	Privacy-preserving data mining.	
Ano de publicação: 	2009	
Fonte/Imprenta: 	In: WANG, J. Encyclopedia of data warehousing and mining. 2nd ed. Hershey: Information Science Reference, 2009.	
Volume: 	v. III	
Páginas: 	p. 1582-1588.	
ISBN: 	978-1-60566-011-0	
Idioma: 	Inglês	
Notas: 	Na publicação: Stanley R. M. Oliveira.	
Conteúdo: 	Despite its benefits in various areas (e.g., business, medical analysis, scientific data analysis, etc), the use of data mining techniques can also result in new threats to privacy and information security. The problem is not data mining itself, but the way data mining is done. "Data mining results rarely violate privacy, as they generally reveal high-Ievel knowledge rather than disclosing instances of data" (Vaidya & Clifton, 2003). However, the concern among privacy advocates is well founded, as bringing data together to support data mining projects makes misuse easier. Thus, in the absence ofadequate safeguards, the use of data mining can jeopardize the privacy and autonomy of individuals. Privacy-preserving data mining (PPDM) cannot simply be addressed by restricting data collection or even by restricting the secondary use of information technology (Brankovic & V. Estivill-Castro, 1999). Moreover, there is no exact solution that resolves privacy preservation in data mining. In some applications, solutions for PPDM problems might meet privacy requirements and provide valid data mining results (Oliveira & ZaYane, 2004b). We have witnessed three major landmarks that characterize the progress and success of this new research area: the conceptive landmark, the deployment landmark, and the prospective landmark. The Conceptive landmark characterizes the period in which central figures in the community, such as O'Leary (1995), Piatetsky-Shapiro (1995), and others (Klõsgen, 1995; Clifton & Marks, 1996), investigated the success of knowledge discovery and some of the important areas where it can conflict with privacy concerns. The key finding was that knowledge discovery can open new threats to informational privacy and information security if not done or used properly. The Deployment landmark is the current period in which an increasing number of PPDM techniques have been developed and have been published in refereed conferences. The information available today is spread over countless papers and conference proceedings. The results achieved in the last years are promising and suggest that PPDM will achieve the goals that have been set for it. The Prospective landmark is a new period in which directed efforts toward standardization occur. At this stage, there is no consensus on privacy principles, policies, and requirements as a foundation for the development and deployment of new PPDM techniques. The excessive number of techniques is leading to confusion among developers, practitioners, and others interested in this technology. One of the most important challenges in PPDM now is to establish the groundwork for further research and development in this area.	
Palavras-Chave: 	Data mining; Mineração de dados; Preservação da informação; Privacidade; Privacy; Segurança.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (12156-1) - UPC - PL - PP -  -  - 2008.00150 - DES
CNPTIA - (12156-2) - UPC - PL - DD -  -  -  - DIS