INTRUSION DETECTION SYSTEM USING MACHINE LEARNING AND DEEP LEARNING ALGORITHMS

Abstract

Today with the development of technology and its rapid growth a new concern is beginning to take place: cyber-attacks. This has caused a great concern in every field in all over the world which cause a great trouble in networks and cause the different problems to PC users. Now days many different companies are working to fight these kinds of cyber-attacks by using new techniques to detect them and later to destroy them. Machine learning is the field which gives the computer the ability to learn without being explicitly programmed. There are many different methods how to implement this technology. In this study we will show many different algorithms that are employed to fight against different cyber-attacks. In this paper we will discuss about many types of cyber-attacks, the methods of defense against these cyber-attacks and the classification algorithms that are employed against different kinds of cyber-attacks, their implementation, accuracy and the testing time based on the type of the attack according to classification. In this thesis we will talk about different types of these algorithms.