PROTECTION FROM CYBER ATTACKS USING IDS SECURITY MECHANISM WITH RANDOM FOREST CLASSIFIER: A REVIEW
Abhishek Kajal, Garima Sardana · Journal of Critical Reviews · 2020
This research paper focuses on the threats to web-based services by attackers. These attackers use manual and machine-based methods to perform attacks over the web. They are becoming more powerful and efficient. This paper highly concentrates on Intrusion Detection Systems (IDS). An Intrusion Detection System is a system of protection and threat stoppage technology. It monitors system traffic flows in order to identify and stop the exploitation of weak points. The past research related to IDS has been discussed in this paper. The objective and methodology of existing work has also been explained in this paper. The paper has also considered the scope of IDS system for web security. In our work, we analyze various machine learning based Classifiers that are used to improve the performance of IDS and aim to propose a technique to improve the performance of IDS with support of Random Forest Classifier. Future researches are supposed to evaluate the new technique by calculating the quality of service parameters.