Analysis and Categorization of Emotet IoT Botnet Malware

Abstract

To provide the ease control and remote monitoring, Internet of Things (IoT) plays an important role in smart devices. The IoT system ranges from smart city to healthcare sector, and supply chain management. This extent of advancement generated a huge amount of data which may be the reason of malware threats of the IoT system. IoT Malware is a threat which may affects all sectors such as business, network, telecoms, media, military, etc. The recent report claimed the proliferation of global cost of malware estimated that till 2023 it would be around 8 trillion dollars annually which may double due to coronavirus outbreak. The analysis of IoT malware needs serious concern as now warfare and digital retaliation can cause serious damage than the war lead on ground. The major aim of this paper is performing the critical analysis of an IoT malware named Emotet. The IoT malware analysis can be categorized in two types such as static and dynamic malware analysis. Static analysis is the process of analyzing malware or binary without executing it. It is considered a more effective method when it comes to the diversity of processor architecture. While dynamic analysis is based on the detection of malware and its behavior with real-time execution. This paper focused on the testbed and Analysis of Emotet malware statically and dynamically using distinguished malware analysis tools.