Preventing the Cloud Networks through Semi-Supervised Clustering from Both Sides Attacks

Cloud computing is a centralized data storage system providing various services worldwide. Different organizations are using the cloud for other purposes. As the number of users on the cloud server increases, so does the rate of attacks on the cloud. Various researchers have devised different solutions to solve these problems, the most widely used being the Intrusion Detection System (IDS). In this paper, a network architecture has been designed in which an efficient technique, semi-supervised clustering, has been used. In this technique, users' responses inside and outside the cloud server have been observed, and various rules and mechanisms have been enforced based on these responses. The network is divided into three different scenarios. In the first scenario, attacks outside the cloud server have been detected, and then ways to prevent these attacks are discussed. The second scenario uses Cloud Shell, allowing authentic users to access the cloud server through authentic queries. In the third scenario, this tool's performance and detection rate have been measured by applying different results to the confusion matrix. A comparative analysis has been done with other papers at the end of the paper, and conclusions have been drawn based on different results.

Automated summary

This paper introduces a network architecture that utilizes the efficient technique of semi-supervised clustering to design an intrusion detection system. By observing users' responses inside and outside the cloud server, different rules and mechanisms are enforced to prevent attacks on the cloud server. The research conducts experiments in different scenarios and compares the results with other papers.