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Implementation of RSA with Feed-forward Neural Network using MATLAB

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Somesh Kumar, Rajkumar Goel
10.5120/ijca2016911024

Somesh Kumar and Rajkumar Goel. Implementation of RSA with Feed-forward Neural Network using MATLAB. International Journal of Computer Applications 148(2):22-25, August 2016. BibTeX

@article{10.5120/ijca2016911024,
	author = {Somesh Kumar and Rajkumar Goel},
	title = {Implementation of RSA with Feed-forward Neural Network using MATLAB},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2016},
	volume = {148},
	number = {2},
	month = {Aug},
	year = {2016},
	issn = {0975-8887},
	pages = {22-25},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume148/number2/25730-2016911024},
	doi = {10.5120/ijca2016911024},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

In this paper the RSA algorithm has been implemented with feed forward artificial neural network using MATLAB. This implementation is focused on the network parameters like topology, training algoritahm, no. of hidden layers, no. of neurons in each layer and learning rate in order to get the more efficient results. Many examples are tested and it is obtained that two hidden layers feed forward neural network architectures will lead to optimal solution. Our goal in this paper is to obtain the minimum training time and minimum number of training iterations using the proposed optimal solution.

References

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Keywords

RSA, Neural Network