IoT Botnet Creation and Detection using Machine Learning

Abstract

According to ethical hacking specialists, malware has been present in online environments for a very long time. More malware is being disseminated online as new technology is developed. The prevalence of botnets has increased. Infected software first creates a botnet before spreading the bot throughout a network. A botnet is employed in scenarios with infected massive computers. Ethical hacking instructors issue a warning due to the botnet’s ability to infect vast numbers of computers. Cybersecurity is increasingly relying on botnets. Botnets attack the vast majority of enterprises. To tackle this issue, researchers began to use machine learning (ML).We give a quick review of the various machine learning (ML) techniques used in botnet identification in this study. This paper’s main goal is to undertake various malware analysis to build our botnet, analyze it using a packet-capturing tool, and further validate our machine-learning models utilizing the botnet. To develop reliable and effective real-time online detection and mitigation systems as well as more reliable models, a comprehensive knowledge of these functions is essential.