A Novel Approach to Synchronization Problem of Artificial Neural Network in Cryptography
نویسنده
چکیده
t is becoming increasingly difficult to have data security nowadays. There have been used various cryptography methods in literature, but recent developments in computational area have heightened the need of new methods. In this study the feed-forward artificial neural network (FFNN) was used with a different perspective by using the structure of artificial neural network as a key as a solution of synchronization problem of FFNNs in cryptography. The proposed method was employed for text, audio and image data and the results were found acceptable. Also, the results of FFNN were assessed with the results of probabilistic, radial basis artificial neural networks and k nearest neighbor and wavelet transforms. The FFNN was faster than these methods and had 100% decryption accuracy.
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