A Review of Cloud-based-Malware-Detection using Artificial Intelligence in the Cyber Domain

Artificial intelligence techniques have advanced rapidly in recent years, and their practical applications can be found in a wide range of fields, from facial recognition to image analysis. In order to target the user, malware writers are now attempting to write more progressive, sophisticated malware. In the field of cybersecurity, AI-based techniques can help adversaries improve malware attack methods and provide better cyber defence tools. Because the majority of this malware is refined versions of its predecessors, traditional security solutions such as anti-viruses and anti-malware fail to detect it. Furthermore, in order to complete their operations, these solutions consume a large amount of computational resources on the host. This survey paper aims to provide an overview of how artificial intelligence can be used in both offense and defence in the context of cybersecurity. To avoid detection, a new generation of malware employs advanced obfuscation and packing techniques. Detecting complex malware using traditional detection methods is nearly impossible in this situation. The paper provides an in-depth analysis of cloud-based malware detection methods, as well as a vision of how the cloud can be used to protect the Internet of Things (IoT) and Cyber-Physical Systems (CPS) from cyber-attacks