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Frequent Pattern Technique using Federation Rule Mining
Objectives: To improve the security, as well as privacy while sharing data/information to third parties. From the database Duplicate data were eliminated and extracted the original database Methods/Statistical Analysis: FP tree based algorithm was proposed in this paper. It is used to generate the frequent item data sets. Those frequent data Item sets are extracted by using inverse data item set. It must achieve good security and privacy. Findings: The main problem in existing system is information leakage. In frequent pattern technique, federation rule mining process which tries to find some correlations and associations among the various types of data items in a dataset. It finds more privacy preserving techniques related to the data mining process. Applications/Improvement: To compare and evaluate the proposed of many algorithms, federation rule mining should able to maintain the data privacy in a proper manner.
Federation Rule Mining, Frequent Pattern, Crypt Analysis, Data Contortion, Data Sensation.
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