Chaos-based simultaneous compression and encryption for Hadoop

Data compression and encryption are key components of commonly deployed platforms such as Hadoop. Numerous data compression and encryption tools are presently available on such platforms and the tools are characteristically applied in sequence, i.e., compression followed by encryption or encryption...

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Main Authors: Usama, M., Zakaria, N.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.19710 /
Published: Public Library of Science 2017
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009062996&doi=10.1371%2fjournal.pone.0168207&partnerID=40&md5=294e772a7894882aa50fd3d19283a2d3
http://eprints.utp.edu.my/19710/
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spelling utp-eprints.197102018-04-20T07:33:14Z Chaos-based simultaneous compression and encryption for Hadoop Usama, M. Zakaria, N. Data compression and encryption are key components of commonly deployed platforms such as Hadoop. Numerous data compression and encryption tools are presently available on such platforms and the tools are characteristically applied in sequence, i.e., compression followed by encryption or encryption followed by compression. This paper focuses on the open-source Hadoop framework and proposes a data storage method that efficiently couples data compression with encryption. A simultaneous compression and encryption scheme is introduced that addresses an important implementation issue of source coding based on Tent Map and Piece-wise Linear Chaotic Map (PWLM), which is the infinite precision of real numbers that result from their long products. The approach proposed here solves the implementation issue by removing fractional components that are generated by the long products of real numbers. Moreover, it incorporates a stealth key that performs a cyclic shift in PWLM without compromising compression capabilities. In addition, the proposed approach implements a masking pseudorandom keystream that enhances encryption quality. The proposed algorithm demonstrated a congruent fit within the Hadoop framework, providing robust encryption security and compression. © 2017 Usama, Zakaria. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Public Library of Science 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009062996&doi=10.1371%2fjournal.pone.0168207&partnerID=40&md5=294e772a7894882aa50fd3d19283a2d3 Usama, M. and Zakaria, N. (2017) Chaos-based simultaneous compression and encryption for Hadoop. PLoS ONE, 12 (1). http://eprints.utp.edu.my/19710/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Data compression and encryption are key components of commonly deployed platforms such as Hadoop. Numerous data compression and encryption tools are presently available on such platforms and the tools are characteristically applied in sequence, i.e., compression followed by encryption or encryption followed by compression. This paper focuses on the open-source Hadoop framework and proposes a data storage method that efficiently couples data compression with encryption. A simultaneous compression and encryption scheme is introduced that addresses an important implementation issue of source coding based on Tent Map and Piece-wise Linear Chaotic Map (PWLM), which is the infinite precision of real numbers that result from their long products. The approach proposed here solves the implementation issue by removing fractional components that are generated by the long products of real numbers. Moreover, it incorporates a stealth key that performs a cyclic shift in PWLM without compromising compression capabilities. In addition, the proposed approach implements a masking pseudorandom keystream that enhances encryption quality. The proposed algorithm demonstrated a congruent fit within the Hadoop framework, providing robust encryption security and compression. © 2017 Usama, Zakaria. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
format Article
author Usama, M.
Zakaria, N.
spellingShingle Usama, M.
Zakaria, N.
Chaos-based simultaneous compression and encryption for Hadoop
author_sort Usama, M.
title Chaos-based simultaneous compression and encryption for Hadoop
title_short Chaos-based simultaneous compression and encryption for Hadoop
title_full Chaos-based simultaneous compression and encryption for Hadoop
title_fullStr Chaos-based simultaneous compression and encryption for Hadoop
title_full_unstemmed Chaos-based simultaneous compression and encryption for Hadoop
title_sort chaos-based simultaneous compression and encryption for hadoop
publisher Public Library of Science
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009062996&doi=10.1371%2fjournal.pone.0168207&partnerID=40&md5=294e772a7894882aa50fd3d19283a2d3
http://eprints.utp.edu.my/19710/
_version_ 1741196250597818368
score 11.62408

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