Survey on Privacy-Preserving Mining of Association Rule and Double Encryption Technique
Rutuja Thite, Madan Uttamrao Kharat · Zenodo (CERN European Organization for Nuclear Research) · 2018
Data mining can extract important knowledge from large data collections, but sometimes these collections are split among various parties. Privacy concerns may prevent the parties from directly sharing the data and some types of information about the data. Such data is available is huge amount so it is very difficult to find out the data and relationship among items. For this problem, association rule mining with improved cryptographic technique is one of the solutions of data mining techniques, which can efficiently correlate the items. The output of such technique can be used in many real time applications to take the proper decisions. But the data owner, who shares their data for mutual advantages, wants to secure their data in association rule mining process. Because it can reveal the sensitive data, which might be harmful. Therefore it becomes very challenging task to achieve the security of data while mining the knowledge from it. This paper represents the core idea of privacy preserving association rule mining on vertically partitioned data with use of improved cryptographic technique.