Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
