Industrial Automatic Control Systems and Controllers Annotation << Back Monitoring the Security of the Internet of Things Infrastructure Based on Machine Learning Technologies A.G. Mustafayev The rapid development of technology has enabled billions of devices to connect to the global Internet using both wired and wireless infrastructure. As a result, users and network resources exposed to a large number of potential threats. Particular attention must paid to the security of the Internet of things (IoT), since it includes any objects or devices with network capabilities. IoT technologies play a crucial role in improving real-world smart applications such as smart healthcare, smart homes, smart transportation, and smart education. Traditional mechanisms (firewalls, intrusion detection and prevention systems) are no longer sufficient to protect IoT infrastructure. The unlimited architecture of IoT raises additional concerns related to network access control and software verification. Implementing security measures, such as encryption, authentication, access control, network security, and application security, is inefficient for IoT devices. Therefore, existing security practices must be improved to eff ectively protect the IoT ecosystem. IoT infrastructure provides new attack surfaces caused by interdependent and interconnected IoT environments. For this reason, security in IoT systems should be higher than in other computing systems, and a traditional solution may be ineffective for such systems. Keywords: Internet of things; machine learning; vulnerability; security;, classification. DOI: 10.25791/asu.2.2020.1156 Contacts: - Pp. 36-41.