Detection of IoT Botnet Cyber Attacks using Machine Learning

Since they were first used, systems have faced threats from viruses, worms, and hacking attacks. In 2018, there more devices online than people, this tendency will continue to grow, with an estimated 80 billion by 2024. It is difficult secure equipment the data that flows between them since IoT botnet attacks (IBA) are becoming common. Potential hackers for theft cyberattacks been enticed overwhelming quantity omnipresent presence. One of biggest issues Internet Things security. The main goal research project develop a workable machine learning algorithm-based model identify counteract botnet-based on networks. suggested addresses security concern dangers provided bots. BoT-IoT dataset was used train variety techniques, including linear regression, logistic K-Nearest Neighbor (KNN), SVM models. performance system’s results in F-measure of: 1) 98.0%, 2) 99.0%, 3) 99.0%. 4) This demonstrates proposed models can automatically separate network activities malicious or normal.