A Literature Review on Attacks Prevention and Profiling in Cloud Computing

Abstract

Nowadays, cloud computing is taking more and more part of the services market. However, this technology is still subject to security attacks. In this paper, we aim to provide a literature review on the widely existing solutions for preventing and profiling security attacks in cloud computing and their limitations in detecting different (un)known attacks. Especially, we will discuss the traditional intrusion and prevention systems that have limitations on detecting unknown attacks compared to their capability of detecting and preventing known ones. Therefore, we will draw recommendations and propose by the end a global scheme of a new system that can detect both different known and unknown attacks using machine learning and additional security factors.