Cloud Intrusion Detection System Using Antlion Optimization Algorithm and Support Vector Machine (SVM) Techniques

Abstract

Cloud computing is an emerging technology that provides services and computing resources on demand to users with less management effort through the internet. Because of the increase in the number of internet user and the distributed nature of cloud, it has become a platform for criminal activities from within and outside of cloud environment. It is on this note that Cloud Intrusion Detection System (CIDS) is mostly deployed into cloud environment to identify and also prevent attacks in some instance. In this research work, a cloud intrusion detection system that identifies malicious activities inside cloud, utilizing Antlion Optimization (ALO) algorithm for feature selection and Support Vector Machine Classifier was developed. Experimental result shows 98.56% accuracy, 2.29% FPR, 96.32% (Recall, Precision and F-Measure), and 92.52% Kappa Statistics