DDoS Attack Detection on Cloud Computing Services using Algorithms of Machine Learning: Survey

Abstract

Nowadays cloud computing services have become the most popular internet-based computing and many organizations use their services. Due to this, many cyber-attacks are happening in the cloud. One of those attacks is the Distributed-Denial-Of-Service (DDoS) attack. It floods unreal traffic, hence troubles the availability of the resources. This article is about DDoS attacks and detection of DDoS attacks using machine learning. There are many famous machine learning algorithms such as naïve bayes, random forest, support vector machines etc. These machine learning algorithms can be used to detect the DDoS attacks on doud. There are several datasets available for the researchers to test their proposed models which include NSL-KDD, ICDX, CIDDS-001, CICIDS 2017 etc. This paper presents a detailed study on different Machine learning based techniques proposed by various authors to detect the DDoS attack in the cloud environment. A brief explanation has been provided on the available datasets and further discussed about the general methodology.