TO SECURE M-PLAYERS IN ASSOCIATION RULE MINING TECHNIQUES IN DISTRIBUTED DATABASES

SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 1 (2), JUNE 2020 PP. (85-89)
Abstract– Data mining technology is one of the fastest-growing technologies currently available. This technology is used to extract the most critical and relevant information from massive databases. In contrast, databases are segmented using either a horizontal or vertical partitioning technique. In addition, these database collections are dispersed among numerous parties. Association rule mining is rapidly becoming one of the most significant techniques in the world of data mining. This study presents a protocol for safe association rule mining approaches in horizontal large – scale datasets, based on the Fast distributed Mining (FDM) algorithm, which is an unsecured distributed database implementation of the Apriori algorithm. Two unique, secure multi-party algorithms for mining association rules constitute the major components of this protocol. One of these algorithms computes the union of private subsets held by each interacting player, while the other determines if an element held by one player is contained in a subset held by another. Based on multi algorithms, our method increased the amount of privacy of consumers. In addition, our protocol is simpler to comprehend and more efficient than previous methods in terms of the number of communication rounds, the cost, and the computational cost.
Index Terms – Apriori Algorithm, multi-party algorithm, FDM, Distributed database, Association ru
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Arunkumar R, Ananthi P, J Shree Smeka
Department of Information Technology
Department of Artificial Intelligence and Data Science
Rathinam Technical Campus,
Coimbatore, Tamilnadu, India

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