• DocumentCode
    1784867
  • Title

    Chaotic neural networks for intelligent signal encryption

  • Author

    Chatzidakis, Stylianos ; Forsberg, Per ; Tsoukalas, L.H.

  • Author_Institution
    Sch. of Nucl. Eng., Purdue Univ., West Lafayette, IN, USA
  • fYear
    2014
  • fDate
    7-9 July 2014
  • Firstpage
    100
  • Lastpage
    105
  • Abstract
    The non-linear capabilities of artificial neural networks coupled with the noise-like properties of chaotic systems are exploited to perform signal encryption. The proposed approach computes the signal digital envelope which consists of the encrypted signal, the secret key and the associated hash value. The methodology is demonstrated via the encryption and subsequent decryption of two frequently occurring radiation signals, Co-60 and Cs-137. The results obtained demonstrate the capability of the proposed methodology to couple artificial neural networks and chaos dynamics to produce the signal digital envelope and satisfy the security requirements of confidentiality, authentication, and non-repudiation.
  • Keywords
    cryptography; neural nets; signal processing; artificial neural networks; authentication requirement; chaotic neural networks; confidentiality requirement; decryption; intelligent signal encryption; nonrepudiation requirement; radiation signals; signal digital envelope; Artificial neural networks; Chaotic communication; Encryption; Time series analysis; chaotic systems; neural networks; signal encryption;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information, Intelligence, Systems and Applications, IISA 2014, The 5th International Conference on
  • Conference_Location
    Chania
  • Type

    conf

  • DOI
    10.1109/IISA.2014.6878823
  • Filename
    6878823