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Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective

Hadoop has become a promising platform to reliably process and store big data. It provides flexible and low cost services to huge data through Hadoop Distributed File System (HDFS) storage. Unfortunately, absence of any inherent security mechanism in Hadoop increases the possibility of malicious att...

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Autores principales: Kapil, Gayatri, Agrawal, Alka, Attaallah, Abdulaziz, Algarni, Abdullah, Kumar, Rajeev, Khan, Raees Ahmad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924543/
https://www.ncbi.nlm.nih.gov/pubmed/33816911
http://dx.doi.org/10.7717/peerj-cs.259
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author Kapil, Gayatri
Agrawal, Alka
Attaallah, Abdulaziz
Algarni, Abdullah
Kumar, Rajeev
Khan, Raees Ahmad
author_facet Kapil, Gayatri
Agrawal, Alka
Attaallah, Abdulaziz
Algarni, Abdullah
Kumar, Rajeev
Khan, Raees Ahmad
author_sort Kapil, Gayatri
collection PubMed
description Hadoop has become a promising platform to reliably process and store big data. It provides flexible and low cost services to huge data through Hadoop Distributed File System (HDFS) storage. Unfortunately, absence of any inherent security mechanism in Hadoop increases the possibility of malicious attacks on the data processed or stored through Hadoop. In this scenario, securing the data stored in HDFS becomes a challenging task. Hence, researchers and practitioners have intensified their efforts in working on mechanisms that would protect user’s information collated in HDFS. This has led to the development of numerous encryption-decryption algorithms but their performance decreases as the file size increases. In the present study, the authors have enlisted a methodology to solve the issue of data security in Hadoop storage. The authors have integrated Attribute Based Encryption with the honey encryption on Hadoop, i.e., Attribute Based Honey Encryption (ABHE). This approach works on files that are encoded inside the HDFS and decoded inside the Mapper. In addition, the authors have evaluated the proposed ABHE algorithm by performing encryption-decryption on different sizes of files and have compared the same with existing ones including AES and AES with OTP algorithms. The ABHE algorithm shows considerable improvement in performance during the encryption-decryption of files.
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spelling pubmed-79245432021-04-02 Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective Kapil, Gayatri Agrawal, Alka Attaallah, Abdulaziz Algarni, Abdullah Kumar, Rajeev Khan, Raees Ahmad PeerJ Comput Sci Cryptography Hadoop has become a promising platform to reliably process and store big data. It provides flexible and low cost services to huge data through Hadoop Distributed File System (HDFS) storage. Unfortunately, absence of any inherent security mechanism in Hadoop increases the possibility of malicious attacks on the data processed or stored through Hadoop. In this scenario, securing the data stored in HDFS becomes a challenging task. Hence, researchers and practitioners have intensified their efforts in working on mechanisms that would protect user’s information collated in HDFS. This has led to the development of numerous encryption-decryption algorithms but their performance decreases as the file size increases. In the present study, the authors have enlisted a methodology to solve the issue of data security in Hadoop storage. The authors have integrated Attribute Based Encryption with the honey encryption on Hadoop, i.e., Attribute Based Honey Encryption (ABHE). This approach works on files that are encoded inside the HDFS and decoded inside the Mapper. In addition, the authors have evaluated the proposed ABHE algorithm by performing encryption-decryption on different sizes of files and have compared the same with existing ones including AES and AES with OTP algorithms. The ABHE algorithm shows considerable improvement in performance during the encryption-decryption of files. PeerJ Inc. 2020-02-17 /pmc/articles/PMC7924543/ /pubmed/33816911 http://dx.doi.org/10.7717/peerj-cs.259 Text en ©2020 Kapil et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Cryptography
Kapil, Gayatri
Agrawal, Alka
Attaallah, Abdulaziz
Algarni, Abdullah
Kumar, Rajeev
Khan, Raees Ahmad
Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective
title Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective
title_full Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective
title_fullStr Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective
title_full_unstemmed Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective
title_short Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective
title_sort attribute based honey encryption algorithm for securing big data: hadoop distributed file system perspective
topic Cryptography
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924543/
https://www.ncbi.nlm.nih.gov/pubmed/33816911
http://dx.doi.org/10.7717/peerj-cs.259
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