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http://dx.doi.org/10.13089/JKIISC.2019.29.6.1305

Analysis of Encryption Algorithm Performance by Workload in BigData Platform  

Lee, Sunju (Department of Software Security, Korea University Graduate School of Computer & Information Technology)
Hur, Junbeom (Department of Computer Science and Engineering, Korea University College of Informatics)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.29, no.6, 2019 , pp. 1305-1317 More about this Journal
Abstract
Although encryption for data protection is essential in the big data platform environment of public institutions and corporations, much performance verification studies on encryption algorithms considering actual big data workloads have not been conducted. In this paper, we analyzed the performance change of AES, ARIA, and 3DES for each of six workloads of big data by adding data and nodes in MongoDB environment. This enables us to identify the optimal block-based cryptographic algorithm for each workload in the big data platform environment, and test the performance of MongoDB by testing various workloads in data and node configurations using the NoSQL Database Benchmark (YCSB). We propose an optimized architecture that takes into account.
Keywords
MongoDB; Encryption; BigData; NoSQL; YCSB;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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