Abstract
In this paper, we propose Device Authentication Code (DAC), a novel method for authenticating IoT devices with wireless interface, by exploiting their radio frequency (RF) signatures. The proposed DAC is based on RF fingerprinting, an information-theoretic method, feature learning, and the discrimi
Highlights
Given the proliferation of complex and heterogeneous networks such as 5G, and the Internet-of-Things (IoT) paradigm, the number of deployed wireless devices are expected to grow exponentially in the near future
To validate the ideas presented in this work, radio frequency (RF) traces were collected from three types of devices: (1) six MICAz-MPR2400 sensors, (2) NI universal software radio peripheral (USRP)-293x and (3) USRP X310 Software Defined Radio (SDR) Devices
We propose a novel framework for intrusion detection based on RF fingerprinting using deep learning
Summary
Given the proliferation of complex and heterogeneous networks such as 5G, and the Internet-of-Things (IoT) paradigm, the number of deployed wireless devices are expected to grow exponentially in the near future. While the success of authentication techniques based on pairwise key confirmation has been demonstrated in examples such as cryptosystem, key management still faces a number of challenges when implemented in dynamic wireless communication networks. Studies were conducted which focused on extracting characteristics of the communication signals to detect unauthorized transmitters in the VHF FM spectrum range. This gave rise to research on RF fingerprinting technologies, and subsequent design of RF fingerprint extraction and authentication methods. The focus is on two major phases of RF fingerprinting: (1) wireless transmitter RF fingerprint extraction, and (2) RF fingerprint authentication
Sign-in/Register to view highlights & summary 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.
