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Efficient Big Data Modelling and Organization for Hadoop Hive-Based Data Warehouses Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Using Homomorphic Encryption to Compute Privacy Preserving Data Mining in a Cloud Computing Environment

Authors : Hamza Hammami, Hanen Brahmi, Imen Brahmi, Sadok Ben Yahia

Published in: Information Systems

Publisher: Springer International Publishing

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Abstract

Cloud computing refers to an information technology infrastructure where data and software are stored and processed in a remote data center, accessible as a service through the Internet. Typical data centers within these fields are large, complex and often noisy. Further-more, privacy preserving data mining is an important challenge. It is required to protect the confidentiality of data sources during the extraction of frequent closed patterns. In fact, no site should be able to learn contents of a transaction at any other site. The work carried out in this paper deals with this problem. In this context, we suggest an approach that combines the extraction of frequent closed patterns in a distributed environment such as the cloud. We aim at maintaining the privacy of the sites during the data mining task in a cloud environment based on homomorphic encryption. The Simulation results and performance analysis show that our mechanism requires less communication and computation overheads. It can effectively preserve data privacy, check data integrity, and ensures high data transmission efficiency.

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previous chapter A Security Approach for Data Migration in Cloud Computing Based on Human Genetics
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Metadata
Title
Using Homomorphic Encryption to Compute Privacy Preserving Data Mining in a Cloud Computing Environment
Authors
Hamza Hammami
Hanen Brahmi
Imen Brahmi
Sadok Ben Yahia
Copyright Year
2017
Book
Information Systems

Print ISBN: 978-3-319-65929-9

Electronic ISBN: 978-3-319-65930-5

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-65930-5_32

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