DocumentCode :
1566853
Title :
Privacy Preserving Support Vector Machines in Wireless Sensor Networks
Author :
Kim, Dong Seong ; Azim, Muhammad Anwarul ; Park, Jong Sou
Author_Institution :
Network & Embedded Security Lab., Korea Aerosp. Univ., Goyang
fYear :
2008
Firstpage :
1260
Lastpage :
1265
Abstract :
It is important to achieve energy efficient data mining in Wireless Sensor Networks (WSN) while preserving privacy of data. In this paper, we present a privacy preserving data mining based on Support Vector Machines (SVM). We review the previous approach in privacy preserving data mining in distributed system. And we also review energy efficient data mining in WSN. We then propose an energy efficient privacy preserving data mining in WSN. We use SVM because it has been shown best classification accuracy and sparse data presentation using support vectors. We show security analysis and energy estimation of our proposed approach.
Keywords :
data mining; data privacy; support vector machines; wireless sensor networks; data mining; data privacy preservation; sparse data presentation; support vector machines; wireless sensor networks; Availability; Commutation; Data mining; Data privacy; Data security; Energy efficiency; Kernel; Support vector machine classification; Support vector machines; Wireless sensor networks; Sensor networks; data mining; energy efficiency; privacy preserving data mining; security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Availability, Reliability and Security, 2008. ARES 08. Third International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-0-7695-3102-1
Type :
conf
DOI :
10.1109/ARES.2008.151
Filename :
4529488
Link To Document :
بازگشت