Cloud-Based Malware Detection Using Machine Learning Methods

Abstract

Malware in the cloud can affect many users on multiple platforms, while traditional malware typically only affects a system or a small number of users. In addition, malware in the cloud can hide in cloud services or user accounts, making it more difficult to detect and remove than traditional malware. Information security solutions installed on servers (such as anti-malware solutions) are not considered very effective as malware (especially sophisticated solutions) can bypass the detection capabilities of these solutions. Moreover, these solutions often cannot detect new and unknown malware patterns. To address this issue, machine learning (ML) methods have been used and proven effective in detecting malware in many different cases. This chapter per the authors focuses on introducing malware detection techniques in the cloud and evaluating the effectiveness of machine learning methods used, as well as proposing an effective model to support malware detection in the cloud.