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A Bitwise Design and Implementation for Privacy-Preserving Data Mining: From Atomic Operations to Advanced Algorithms

Authors
Song, Baek KyungYoo, Joon SooHong, MiyeonYoon, Ji Won
Issue Date
16-10월-2019
Publisher
WILEY-HINDAWI
Citation
SECURITY AND COMMUNICATION NETWORKS, v.2019
Indexed
SCIE
SCOPUS
Journal Title
SECURITY AND COMMUNICATION NETWORKS
Volume
2019
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/62502
DOI
10.1155/2019/3648671
ISSN
1939-0114
Abstract
Homomorphic encryption (HE) is considered as one of the most powerful solutions to securely protect clients' data from malicious users and even severs in the cloud computing. However, though it is known that HE can protect the data in theory, it has not been well utilized because many operations of HE are too slow, especially multiplication. In addition, existing data mining research studies using encrypted data focus on implementing only specific algorithms without addressing the fundamental problem of HE. In this paper, we propose a fundamental design and implementation of data mining algorithm through logical gates. In order to do this, we design various logic of atomic operations in encrypted domain and finally apply these logic to well-known data mining algorithms. We also analyze the execution time of atomic and advanced algorithms.
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