• DocumentCode
    2213822
  • Title

    A Chaotic Images Encryption Algorithm with the Key Mixing Proportion Factor

  • Author

    Enzeng, Dong ; Zengqiang, Chen ; Zhuzhi, Yuan ; Zaiping, Chen

  • Author_Institution
    Dept. of Autom., Tianjin Univ. of Technol., Tianjin
  • Volume
    1
  • fYear
    2008
  • fDate
    19-21 Dec. 2008
  • Firstpage
    169
  • Lastpage
    174
  • Abstract
    The pseudo random property of chaotic sequences is very useful in the field of information security, based on the idea of orbit hopping, a chaotic image encryption algorithm with a key mixing proportion factor is proposed. In the proposed algorithm the position scrambling matrix and the value scrambling matrix are generated by the improved chaotic logistic sequences. A key mixing proportion factor (KMPF) is generated based on the plaintext information. By adding this factor, most of cipher text elements value can be changed by the change of any plaintext element. The Security of the proposed algorithm is improved with this factor, and the ability of the proposed algorithm resisting plaintext attacks is strengthened obviously, and the encryption algorithm can resist the statistical and differential attacks effectively, moreover, the algorithm has a large key space and high encryption speed. The effectiveness of the proposed algorithm is verified by the theoretical analysis and numerical simulations.
  • Keywords
    cryptography; image processing; numerical analysis; security of data; chaotic images encryption algorithm; encryption algorithm; information security; numerical simulations; plaintext information; position scrambling matrix; value scrambling matrix; Algorithm design and analysis; Automation; Chaos; Cryptography; Equations; Information security; Logistics; Numerical simulation; Probability distribution; Resists;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Management, Innovation Management and Industrial Engineering, 2008. ICIII '08. International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-0-7695-3435-0
  • Type

    conf

  • DOI
    10.1109/ICIII.2008.25
  • Filename
    4737520