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A Study about FP-growth on a Distributed System Using Homomorphic Encryption

Authors:
Mayuko Tanemura
Masato Oguchi

Keywords: Fully Homomorphic Encryption; Data Mining; Distributed System.

Abstract:
Large data collection, such as big data is utilized and analyzed in business. Because large-scale data calculations require a computer system with high processing power, it is practical to outsource the processing to an external server. However, especially when consigning confidential data, such as personal information, it is important to take measures against information leakage. There are various methods, such as data anonymization processing for privacy protection, but in this research, as a method of data confidentiality protection, a Fully Homomorphic Encryption (FHE) that can be calculated in an encrypted state is used. As in a previous study, P3CC is used, which applies FHE to a client-server type system that performs frequent pattern mining with the Apriori algorithm. To implement this system, the Apriori algorithm is changed to the FP-growth algorithm in our research work, and the results are compared with those of the existing method using the Apriori algorithm.

Pages: 96 to 100

Copyright: Copyright (c) IARIA, 2019

Publication date: October 27, 2019

Published in: conference

ISSN: 2162-2116

ISBN: 978-1-61208-746-7

Location: Nice, France

Dates: from October 27, 2019 to October 31, 2019