Malware analysis in IoT devices and AI

The Internet of Things (IoT) is an exciting new technology that has the potential to revolutionize many industries. The absence of security for IoT devices has resulted in a rise of malware attacks causing cyber security vulnerabilities for the IoT sector. It is becoming more difficult to find systematic and complete research on the relevance of malware detection techniques in IoT environments, such as those involving Trojans or botnets. This study was conducted to compile a comprehensive list of experimental studies relevant to the detection of malware attacks in the IoT, as well as to evaluate and critique those studies. A systematic literature review methodology introduced was used to obtain and critically assess research publications to achieve this aim. Detection approaches for malware, types of botnet attacks, and diverse harmful behaviors of malware were examined in this study. The detection approaches have been categorized depending on the methodologies utilized, and the authors analyzed the malware stages in which detection is performed. To build a foundation of information about IoT malware detection technologies, the findings of this study have helped the authors identify the research gaps in the field and recommended future research options.