Chaotic neural networks for intelligent signal encryption
Stylianos Chatzidakis, P. Forsberg, Lefteri H. Tsoukalas · 2014
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.