DocumentCode :
2919211
Title :
Using Homomorphic Encryption and Digital Envelope Techniques for Privacy Preserving Collaborative Sequential Pattern Mining
Author :
Zhan, Justin
Author_Institution :
Carnegie Mellon Univ., Pittsburgh
fYear :
2007
fDate :
23-24 May 2007
Firstpage :
331
Lastpage :
334
Abstract :
Nowadays, data mining is widely used in various applications. Privacy is an important issue in data mining systems. By privacy, we mean how to conduct data mining without compromising much data privacy. In particular, we consider the scenario where data sharing for data mining purpose is the main goal. However, we would like minimize the data disclosure during data mining process.
Keywords :
cryptography; data mining; data privacy; data mining; digital envelope techniques; homomorphic encryption; privacy preserving collaborative sequential pattern mining; Collaboration; Cryptography; Data mining; Data privacy; Databases; Explosions; Internet; Protocols;
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.2007.379493
Filename :
4258719
Link To Document :
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