Enhancing Intrusion Detection Using Statistical Functions

Abstract

Intrusion detection has become an issue of concern on the Internet recently. With the excessive growth of Internet, it is clear that organizations should seek to defend themselves of the best possible protection alongside illegal entry; moreover, the problem in this research seeks to solve the strategy outsiders deploy to outwit detection systems by dividing the packets into smaller patterns to avoid being detected. The research aimed to specify a mathematical model to enhance the intrusion detection process. In this paper mathematical function have been used together and a system was implemented to prove the model applicability. Probability laws, mode calculation, slandered deviation, and the median calculation have been used through mathematical module to get an accurate measures and results to classify the incoming data and provide more immunity to the intrusion detection system. The detection tool was developed under MATLAB 2016 in order to simulate the previous mathematical rules, and obtain positive results that indicated the system–s capability to enhancing intrusion detection. The system has achieved a convenient result which proofs the idea behind mathematical functions utilization in such field; network security.