Safely delegating data mining tasks


Autoria(s): Qui, Ling; Ong, Kok-Leong; Lui, Sui Man
Contribuinte(s)

Christen, Peter

Kennedy, Paul J.

Li, Jiuyong

Simoff, Simeon J.

Williams, Graham J.

Data(s)

01/01/2006

Resumo

Data mining is playing an important role in decision making for business activities and governmental administration. Since many organizations or their divisions do not possess the in-house expertise and infrastructure for data mining, it is beneficial to delegate data mining tasks to external service providers. However, the organizations or divisions may lose of private information during the delegating process. In this paper, we present a Bloom filter based solution to enable organizations or their divisions to delegate the tasks of mining association rules while protecting data privacy. Our approach can achieve high precision in data mining by only trading-off storage requirements, instead of by trading-off the level of privacy preserving.<br />

Identificador

http://hdl.handle.net/10536/DRO/DU:30009760

Idioma(s)

eng

Publicador

Australian Computer Society

Relação

http://dro.deakin.edu.au/eserv/DU:30009760/ong-safelydelegatingdata-2007.pdf

http://www.google.com.au/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fportal.acm.org%2Fcitation.cfm%3Fid%3D1273809&ei=6UinSeu5D5js6QPStIy0Cw&usg=AFQjCNFZRe1kmUPR6WPRNF5ezbkaDlgdsg&sig2=RYbz5WCVNSx_NZX0nnfkzA

Direitos

2006

Palavras-Chave #delegating #privacy preserving #Bloom filter #data mining
Tipo

Conference Paper