In-cloud malware analysis and detection: State of the art

Abstract

With the advent of Internet of Things, we are facing another wave of malware attacks, that encompass intelligent embedded devices. Because of the limited energy resources, running a complete malware detector on these devices is quite challenging. There is a need to devise new techniques to detect malware on these devices. Malware detection is one of the services that can be provided as an in-cloud service. This paper reviews current such systems, discusses there pros and cons, and recommends an improved in-cloud malware analysis and detection system. We introduce a new three layered hybrid system with a lightweight antimalware engine. These features can provide faster malware detection response time, shield the client from malware and reduce the bandwidth between the client and the cloud, compared to other such systems. The paper serves as a motivation for improving the current and developing new techniques for in-cloud malware analysis and detection system. © 2021 Elsevier B.V., All rights reserved.