Enhancing security measures for student-involved system using stochastic random process methodology compared with Petri net Process

An IDS (intrusion detection system) keeps an eye on all of a network’s data packets for any signs of unusual behavior and sends out warnings when it finds anything out of the ordinary. The project’s overarching goal is to use the Probabilistic Randomized Method and the Artificial Network System to detect fraudulent activities in student interactive systems. In each case, a sample size of 10 was used to identify attacks on networks employing the Stochastic Random Process (SRP). A programme called Jupyter Notebook is implemented. By comparing the SRP with the Petri-Net-Process (PNP), we can determine the efficacy of its precision in identifying intrusions. The python programming language is used to create the suggested system, while the spss tool is used for data analysis. In terms of accuracy, the SRP method outperforms the other method by a wide margin (94%). According to the data, dependability in different-sample testing is shown when the significance level is less than 0.05. Intrusion Detection System may be hardware or software component to identify unauthorized access. The Stochastic Random process approach produces a better accuracy rate than the Petri Net Process.