Title :
Using Homomorphic Encryption and Digital Envelope Techniques for Privacy Preserving Collaborative Sequential Pattern Mining
Author_Institution :
Carnegie Mellon Univ., Pittsburgh
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;
Conference_Titel :
Intelligence and Security Informatics, 2007 IEEE
Conference_Location :
New Brunswick, NJ
Electronic_ISBN :
1-4244-1329-X
DOI :
10.1109/ISI.2007.379493