RADTEC: Re-authentication of IoT Devices with Machine Learning

The use of Internet of Things (IoT) devices is higher than ever and is growing rapidly. Many IoT devices are manufactured by home appliance manufacturers where security and privacy is not the foremost concern. There does not exist a strict authentication method that verifies the identity of the device. This allows any rogue IoT device to authenticate and spoof various IoT device activities using compromised credentials. This paper addresses the issue by introducing a novel method for re- and continuous authentication utilizing a device-type classification as a new identity paradigm. We present RADTEC: a protocol for authenticating a device in a network by leveraging machine learning to classify the type of an IoT device attempting to connect to the network with an accuracy of over 95% in less than 0.65 milliseconds. We investigate multiple machine learning classifiers to infer the types of IoT devices and use them to develop a stricter and more efficient method for authentication.