Construction of Early Warning Mechanism of University Education Network Based on the Markov Model

Abstract

This paper proposes and builds an early warning mechanism model of the college education network using the Markov model. This paper proposes a method to determine the observation value of Markov model based on the flow control principle and TCP/IP model in an effort to address the issue that the observation value of Markov model is challenging to determine when it is applied to intrusion detection. The detection model also employs an adaptive sliding detection window algorithm to further increase the system’s detection rate. The mechanism developed in this paper is compared to other early warning mechanisms in order to confirm the validity and applicability of the educational network early warning mechanism. The experimental results demonstrate that the accuracy of the educational network early warning mechanism in this paper is higher than that of the conventional early warning mechanism, which is 9.87 percent, at up to 95.02 percent. The proposed model, however, clearly excels in terms of early warning adaptability, model fitting level, and information overload processing effectiveness. In general, this paper successfully applies the Markov model to the early warning system of the college education network. For the study of the college education network’s early warning system, it has some reference value.