Development of Machine Learning Based Security Algorithm for 4G Network against Wormhole

Eze E.M., Ituma C., Asogwa T.c and Ebere U.C.
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Eze E.M.: Enugu State University of Science and Technology
Ituma C.: Enugu State University of Science and Technology
Asogwa T.c: Enugu State University of Science and Technology
Ebere U.C.: Destinet Smart Technologies Ltd.

International Journal of Research and Innovation in Applied Science, 2022, vol. 7, issue 2, 70-75

Abstract: TThis work development of machine learning based security algorithm for 4G network against wormhole. This was achieved using methods such as data collection, data extraction, training and classification process. The system design employed mathematical and structural method to develop the models of the wormhole and also the new security algorithm using artificial neural network. This was implemented with Simulink and neural network toolbox, before testing. The result showed that the algorithm was able to detect wormhole at a regression of 0.9978 and Mean square error of 2.05×10^-5. The security algorithm deployed on a 4G network and tested; the result showed that throughput percentage of 89.16% and latency of 76.325ms which according to International Telecommunication Union (ITU-U) and Nigerian Communication Commission standard (NCC) are good.

Date: 2022
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