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

Gayatri Kapil1, Alka Agrawal1, Abdulaziz Attaallah2

  • 1Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India.

Peerj. Computer Science
|April 5, 2021
PubMed
Summary
This summary is machine-generated.

Attribute Based Honey Encryption (ABHE) enhances Hadoop security by integrating attribute-based and honey encryption methods. This novel approach improves data security and encryption-decryption performance for large files stored in Hadoop Distributed File System (HDFS).

Keywords:
And encryption-decryptionBig dataCloud storageData securityHDFSHadoop

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Area of Science:

  • Big Data Security
  • Distributed Systems
  • Cryptography

Background:

  • Hadoop Distributed File System (HDFS) offers scalable big data storage but lacks inherent security mechanisms.
  • Securing data in HDFS is challenging due to potential malicious attacks and the performance degradation of traditional encryption algorithms with increasing file sizes.
  • Existing encryption methods like AES and AES with One-Time Password (OTP) struggle with efficiency in large-scale data environments.

Purpose of the Study:

  • To address the critical data security challenges in Hadoop storage.
  • To propose and evaluate a novel encryption methodology that overcomes the performance limitations of existing algorithms for large files.
  • To enhance the protection of user information stored within the Hadoop ecosystem.

Main Methods:

  • Integration of Attribute Based Encryption (ABE) with honey encryption techniques, termed Attribute Based Honey Encryption (ABHE).
  • Implementation of ABHE for encoding files within HDFS and decoding them within the Mapper component.
  • Comparative performance analysis of ABHE against established algorithms such as Advanced Encryption Standard (AES) and AES with OTP.

Main Results:

  • The proposed Attribute Based Honey Encryption (ABHE) algorithm demonstrates significant improvements in encryption-decryption performance.
  • ABHE shows enhanced efficiency when processing files of varying sizes, outperforming traditional methods like AES.
  • The methodology effectively addresses the scalability and performance issues associated with encrypting large datasets in HDFS.

Conclusions:

  • Attribute Based Honey Encryption (ABHE) offers a robust and efficient solution for securing big data stored in Hadoop.
  • The integration of ABE and honey encryption provides a promising approach to overcome the performance bottlenecks of conventional encryption methods in distributed storage systems.
  • ABHE represents a valuable advancement in ensuring data confidentiality and integrity within the Hadoop environment.