Secure extraction of association rules in horizontally distributed database using improved UNIFI

Abstract

Data extraction is used to extract important data from large database which stored at the multiple sites. It may be keep in many computers covered in the some physical location or may be covered a network of computers. In this paper, we present protocol for secure extraction of association rules in horizontally distributed database. This protocol is based on the Fast Distributed Mining (FDM) algorithm, using concept of encryption and decryption for extraction of knowledge. Here, we present Improved UNIFI algorithm for secure extraction of association rules. The objective of the protocol is to overcome the problem of extraction of association rules that simulates the existing system i.e grants frequent itemset recognition without candidate itemset generation. This protocol uses support, confidence threshold value and for security and privacy purpose used AES encryption, decryption standard which is symmetric block cipher. It is simple and important in terms of communication rounds as well as communication and computational cost.

Cite this paper

@article{More2017SecureEO, title={Secure extraction of association rules in horizontally distributed database using improved UNIFI}, author={Vidya R. More and Balkrishna K. Patil and Rajesh A. Auti}, journal={2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC)}, year={2017}, pages={205-210} }