Problem statement: This paper examines Artificial Spiking Neural Network
(ASNN) which inter-connects group of artificial neurons that uses a
mathematical model with the aid of block cipher. The aim of undertaken this
research is to come up with a block cipher where by the keys are randomly
generated by ASNN which can then have any variable block length. This will show
the private key is kept and do not have to be exchange to the other side of the
communication channel so it present a more secure procedure of key scheduling.
The process enables for a faster change in encryption keys and a network level
encryption to be implemented at a high speed without the headache of
factorization. Approach: The block cipher is converted in public cryptosystem
and had a low level of vulnerability to attack from brute, and moreover can
able to defend against linear attacks since the Artificial Neural Networks
(ANN) architecture convey non-linearity to the encryption/decryption
procedures. Result: In this paper is present to use the Spiking Neural Networks
(SNNs) with spiking neurons as its basic unit. The timing for the SNNs is
considered and the output is encoded in 1's and 0's depending on the occurrence
or not occurrence of spikes as well as the spiking neural networks use a sign
function as activation function, and present the weights and the filter
coefficients to be adjust, having more degrees of freedom than the classical
neural networks. Conclusion: In conclusion therefore, encryption algorithm can
be deployed in communication and security applications where data transfers are
most crucial. So this paper, the neural block cipher proposed where the keys
are generated by the SNN and the seed is considered the public key which
generates the both keys on both sides In future therefore a new research will
be conducted on the Spiking Neural Network (SNN) impacts on communication.