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An Asymetric-key Cryptosystem based on Artificial Neural Network

Abstract:

Protect the information has always been important concerns for society, and mainly now in digital era. Currently exists different platforms to manage critical and sensitive information, ranging from bank accounts to social media. All platforms have taken steps to guarantee that the data passing through them is protected from hackers. An essential subject in digital world born, giving place to symmetric and asymmetric key algorithms. Asymmetric key algorithms work by manipulating very big prime numbers, which gives a high level of security but also takes a long time to compute. This paper offers a cryptographic system based on deep learning techniques. The approach avoided the necessity of big prime numbers by using the synaptic weights of an autoencoder neural network as encryption and decryption keys. The suggested method allows for a high amount of unpredictability in the initial and final synaptic weights without compromising the network’s overall performance. The results was shown to be resilient and difficult to break in a theoretical security study with a low computational time.