sis 20(27): e2

Research Article

Performance analysis of compression algorithms for information security: A Review

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  • @ARTICLE{10.4108/eai.13-7-2018.163503,
        author={Neha Sharma and Usha Batra},
        title={Performance analysis of compression algorithms for information security: A Review},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={7},
        number={27},
        publisher={EAI},
        journal_a={SIS},
        year={2020},
        month={3},
        keywords={Data Compression, Huffman Encoding, Information Security Techniques, Lossy Techniques, and Lossless Techniques},
        doi={10.4108/eai.13-7-2018.163503}
    }
    
  • Neha Sharma
    Usha Batra
    Year: 2020
    Performance analysis of compression algorithms for information security: A Review
    SIS
    EAI
    DOI: 10.4108/eai.13-7-2018.163503
Neha Sharma1,*, Usha Batra2
  • 1: Research Scholar, G D Goenka University, 122103, Gurugram, Haryana, India
  • 2: Assistant Dean, G D Goenka University, 122103, Gurugram, Haryana, India
*Contact email: nehasharma0110@gmail.com

Abstract

Data compression is a vital part of information security, since compressed data is much more secure and convenient to handle. Effective data compression technique creates an effective, secure, easy communicable & redundant data. There are two types of compression algorithmic techniques: - lossy and lossless. These techniques can be applied to any data format like text, audio, video or image file. The primary objective of this study was to analyse data compression techniques used for information security techniques like steganography, cryptography etc. Four each, lossy and lossless techniques are implemented and evaluated on parameters like- file size, saving percentage, time, compression ratio and speed. Detailed analysis shows that the lossy techniques performs better quantitatively whereas lossless is better qualitatively. However, lossless techniques are more effective as there is no data loss during the process. Among all, Huffman encoding outperforms other algorithms.