A Network Intrusion Detection System Based on Ensemble Machine Learning Techniques
Prachiti Parkar · 2021
Technology is growing exponentially than ever before; it helps us to make unforeseen progress but at the same time these advancements also pose a grave danger to software systems in terms of security. While paving a path for advancements, these developments are simultaneously lending a helping hand to hackers to hack into systems illegally and misuse the data. While the hackers cannot be stopped, their activities can be identified and prevented. In this paper, I have proposed a simple and effective technique to detect network intrusions and protect valuable data by using Machine Learning algorithms. The novelty in this approach is that the proposed system used the same classifiers in feature selection which were used later for the main classification step, this proved to be fundamental in achieving high accuracy. Moreover, I have successfully simulated attacks in real-time to test our application. Finally, I concluded with fetched results and insights for future research.