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Chidambaram, M.
- Frequent Pattern Technique using Federation Rule Mining
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Authors
Affiliations
1 Department of Computer Science, Bharathiyar University, Coimbatore, Tamil Nadu, IN
2 Computer Science Department, Rajah Serfoji Government College, Thanjavur, Tamil Nadu, IN
1 Department of Computer Science, Bharathiyar University, Coimbatore, Tamil Nadu, IN
2 Computer Science Department, Rajah Serfoji Government College, Thanjavur, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 38 (2016), Pagination:Abstract
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.Keywords
Federation Rule Mining, Frequent Pattern, Crypt Analysis, Data Contortion, Data Sensation.Full Text
- Privacy Preserving Association Rule Mining in Distributed Environments using Fp-Growth Algorithm and Elliptic Curve Cryptography
Abstract Views :172 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, Bharathiyar University, Coimbatore, Tamil Nadu, IN
2 Computer Science Department, Rajah Serfoji Government College, Thanjavur, Tamil Nadu, IN
1 Department of Computer Science, Bharathiyar University, Coimbatore, Tamil Nadu, IN
2 Computer Science Department, Rajah Serfoji Government College, Thanjavur, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 48 (2016), Pagination:Abstract
In this paper, we present a privacy preserving association rule mining method in distributed environments. The proposed method uses FP-growth algorithm and combination of elliptic curve cryptography and digital signature. The proposed method is low in cost for both computation and communication. This method uses associative third party, which is the central authority, holding common cryptographic keys of all the sites and responsible for performing distributed ARM. This method maintains privacy regardless of any number of dishonest sites in the distributed environment.Keywords
Association Rule Mining, ARM, Cryptography, Digital Signature, Elliptic Curve, FP-Growth, Privacy in ARMFull Text