Improved Privacy Preservation with Clustering and Cryptographic Technique in Data Mining

Abstract

Data Mining is the way toward separating knowledge escaped substantial volumes of raw data .The knowledge must be new, not obvious, and one must be able to use it. The primary data is altered by the disinfection procedure to hide sensitive knowledge before discharge so the issue can be addressed. Privacy preservation of delicate knowledge is tended to by a few specialists in the form of association rules via suppressing the frequent item sets. Clustering is technique which makes cluster of useful objects which have resemble characteristics. Anonymization is to protect the identity of the individual this encrypt identifiers like unique number and the name whereas the data which is not encrypted provides less or no guarantee. Advanced Encryption Standard (AES) is an algorithm to provide the security to the data and it is very difficult to apply attacks. By the proposed work, privacy preservation of the data increased and it can be shown with the help of the results. AES provide the result in minimum time which show that propose produce result faster than existing approaches.