DocumentCode :
2919199
Title :
Fast Private Association Rule Mining by A Protocol for Securely Sharing Distributed Data
Author :
Estivill-Castro, Vladimir ; Yasien, Ahmed Haj
Author_Institution :
Griffith Univ., Griffith
fYear :
2007
fDate :
23-24 May 2007
Firstpage :
324
Lastpage :
330
Abstract :
Privacy concerns may discourage users who would otherwise join beneficial data mining tasks for intelligence and/or security. We propose an efficient protocol that allows parties to share data in a private way with no restrictions and without loss of accuracy. Our method has the immediate application that horizontally partitioned databases can be brought together and made public without disclosing the source/owner of each record. At another level, we have an additional benefit that we can apply our protocol to privately discover association rules. Our protocol is more efficient than previous methods. The effects of our protocol are less than others: 1) each party can identify only their data, 2) no party is able to learn the links between other parties and their data, 3) no party learns any transactions of the other parties´ databases.
Keywords :
data mining; data privacy; distributed databases; protocols; public key cryptography; data privacy; horizontally partitioned database; knowledge discovery; private association rule mining; protocol; public key cryptography; securely sharing distributed data; Association rules; Circuits; Clustering algorithms; Collaboration; Data analysis; Data mining; Data privacy; Data security; Protocols; Transaction databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligence and Security Informatics, 2007 IEEE
Conference_Location :
New Brunswick, NJ
Electronic_ISBN :
1-4244-1329-X
Type :
conf
DOI :
10.1109/ISI.2007.379492
Filename :
4258718
Link To Document :
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