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    An efficient secure data compression technique based on chaos and adaptive Huffman coding

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    s12083-020-00981-8.pdf (1.162Mb)
    Date
    2021
    Author
    Usama, Muhammad
    Malluhi, Qutaibah M.
    Zakaria, Nordin
    Razzak, Imran
    Iqbal, Waheed
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    Abstract
    Data stored in physical storage or transferred over a communication channel includes substantial redundancy. Compression techniques cut down the data redundancy to reduce space and communication time. Nevertheless, compression techniques lack proper security measures, e.g., secret key control, leaving the data susceptible to attack. Data encryption is therefore needed to achieve data security in keeping the data unreadable and unaltered through a secret key. This work concentrates on the problems of data compression and encryption collectively without negatively affecting each other. Towards this end, an efficient, secure data compression technique is introduced, which provides cryptographic capabilities for use in combination with an adaptive Huffman coding, pseudorandom keystream generator, and S-Box to achieve confusion and diffusion properties of cryptography into the compression process and overcome the performance issues. Thus, compression is carried out according to a secret key such that the output will be both encrypted and compressed in a single step. The proposed work demonstrated a congruent fit for real-time implementation, providing robust encryption quality and acceptable compression capability. Experiment results are provided to show that the proposed technique is efficient and produces similar space-saving (%) to standard techniques. Security analysis discloses that the proposed technique is susceptible to the secret key and plaintext. Moreover, the ciphertexts produced by the proposed technique successfully passed all NIST tests, which confirm that the 99% confidence level on the randomness of the ciphertext.
    DOI/handle
    http://dx.doi.org/10.1007/s12083-020-00981-8
    http://hdl.handle.net/10576/56771
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    • Computer Science & Engineering [‎2483‎ items ]

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