MODELING OF NEURO BASED STRATEGY FOR MITIGATION OF CYBER THREAT ON 4G WIRELESS NETWORK USING ARTIFICIAL INTELLIGENCE TECHNIQUE

This paper presents modeling of neuro based strategy for the mitigation of cyber threat on 4G wireless network using artificial intelligence technique. The aim was to develop an intelligent botnet detection firewall for the security of 4G network using machine learning. This was achieved using data collection of botnet, feature extraction, artificial neural network, training and classification. The neural network based botnet detection algorithm was modeled with self defining equations and then implemented on a 4G network using Simulink. The result of the algorithm was measured with Receiver Operator Characteristics (ROC), Mean Square Error (MSE) and validated with tenfold cross validation approach. The True Positive Rate from the ROC is 0.9989 while the MSE is 2.7054e-5. The implication of the result showed that algorithm was able to detect botnet correctly with an accuracy of 97.6%.