Design and simulation of threats management model with enhanced users’ networks performance capability

Abstract

In this paper, a model was designed and simulated to effectively detect, prevent, share threat information and log new threats information for investigation beyond users’ networks. This is with a view to addressing threat database growth which degrades users’ networks performance as a result of constant threat update, and lack of expertise to mitigate emerging threats. The model was designed using Mobile Agent (MA), Artificial Neural Network (ANN) and brute force techniques. The simulation of the designed model was carried out in MATLAB 7.0 using NSL-KDD dataset. The performance of the proposed model was evaluated by comparing it with equivalent model when designed as Remote Model Invocation (RMI) based. The metrics used for the evaluation are: response time, bandwidth and fault tolerance. Simulation results showed that the proposed MA model performed better than the RMI model equivalent in all the performance metrics used during simulation. The result showed that the proposed MA model produced encouraging results and a great potentiality to enhance cyberspace protection and users’ networks performance.