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

  • Gayatri Kapil*
  • , Alka Agrawal
  • , Abdulaziz Attaallah
  • , Abdullah Algarni
  • , Rajeev Kumar*
  • , Raees Ahmad Khan
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

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.

Original languageEnglish
Article number259
Pages (from-to)1-31
Number of pages31
JournalPeerJ Computer Science
Volume2020
Issue number2
DOIs
StatePublished - 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 Kapil et al.

Keywords

  • And encryption-decryption
  • Big data
  • Cloud storage
  • Data security
  • HDFS
  • Hadoop

ASJC Scopus subject areas

  • General Computer Science

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