SECURE ASSOCIATION RULE MINING ON VERTICALLY PARTITIONED DATA USING FULLY HOMOMORPHIC ENCRYPTION

ICTACT Journal on Soft Computing ( Volume: 11 , Issue: 4 )

Abstract

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Cloud Computing is a leading innovation technology that guides to access applications over the web. The data owner’s data can be gotten to and controlled in the cloud. Privacy has become conclusive in information-driven applications within the distributed outsourced information. There are numerous inquiries still coming up on the best way to accomplish a confided in a climate that monitors application and information in the cloud from unapproved users. For offering protection to the users, sporadically there is a need to encode the data before accomplishing any other process. The cryptography method is embraced for data privacy. In this paper, a privacy-preserving construction is intended for vertically partitioned data in the cloud with the assistance of the Fully Homomorphic Encryption method. In this work, the homomorphic encryption and the Fully Homomorphic Encryption method is taken into consideration. The performance of the Rule Mining algorithm namely Eclat is compared with the encryption algorithms. The examination result shows that the Fully Homomorphic Encryption is less time-consuming to generate rule in the cloud, regardless of the number of transactions.

Authors

M Yogasini 1, B N Prathibha2
Manonmaniam Sundaranar University, India1, Manonmaniam Sundaranar University, India2

Keywords

Frequent Itemset Mining, Association Rule Mining, Homomorphic Encryption, Fully Homomorphic Encryption

Published By
ICTACT
Published In
ICTACT Journal on Soft Computing
( Volume: 11 , Issue: 4 )
Date of Publication
July 2021
Pages
2424-2428

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