TY - GEN
T1 - Mining information from model build without information disclosure
AU - Sumana, M.
AU - Hareesh, K. S.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - This paper confers an approach of categorizing multiple datasets that are distributed at various sites. The variation in this method of classification is that all the parties jointly build a decision tree model revealing only sufficient information and hiding superfluous data. We have used secure protocols such as secure sum and secure union using commutative encryption technique while model construction. The process discussed in our paper builds efficient, binary classification trees which can in turn predict a test data given by any of the parties involved in the classification.
AB - This paper confers an approach of categorizing multiple datasets that are distributed at various sites. The variation in this method of classification is that all the parties jointly build a decision tree model revealing only sufficient information and hiding superfluous data. We have used secure protocols such as secure sum and secure union using commutative encryption technique while model construction. The process discussed in our paper builds efficient, binary classification trees which can in turn predict a test data given by any of the parties involved in the classification.
UR - https://www.scopus.com/pages/publications/84897053054
UR - https://www.scopus.com/pages/publications/84897053054#tab=citedBy
U2 - 10.1007/978-81-322-1157-0_83
DO - 10.1007/978-81-322-1157-0_83
M3 - Conference contribution
AN - SCOPUS:84897053054
SN - 9788132211563
T3 - Lecture Notes in Electrical Engineering
SP - 819
EP - 827
BT - Emerging Research in Electronics, Computer Science and Technology - Proceedings of International Conference, ICERECT 2012
PB - Springer Verlag
T2 - 1st International Conference on Emerging Research in Electronics, Computer Science and Technology, ICERECT 2012
Y2 - 21 December 2012 through 22 December 2012
ER -