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