This paper presents a physical layer wireless device identification method that uses a convolutional neural network (CNN) operating on a quadrant IQ transition image. This work introduces classification and detection tasks in one process. The proposed method can identify IoT wireless devices by exploiting their RF fingerprints, a technology to identify wireless devices by using unique variations in analog signals. We propose a quadrant IQ image technique to reduce the size of CNN while maintaining accuracy. The CNN utilizes the IQ transition image, which image processing cut out into four-part. An over-the-air experiment is performed on six Zigbee wireless devices to confirm the proposed identification method's validity. The measurement results demonstrate that the proposed method can achieve 99% accuracy with the light-weight CNN model with 36,500 weight parameters in serial use and 146,000 in parallel use. Furthermore, the proposed threshold algorithm can verify the authenticity using one classifier and achieved 80% accuracy for further secured wireless communication. This work also introduces the identification of expanded signals with SNR between 10 to 30dB. As a result, at SNR values above 20dB, the proposals achieve classification and detection accuracies of 87% and 80%, respectively.

We consider secret key agreement for multiple terminals based on radio propagation characteristics in a wireless relaying system where more than two terminals communicate with each other via a relay. In this system, the multiple terminals share a common secret key generated from their radio propagation characteristics with the help of the relay in the presence of an eavesdropper. In this paper, we present three secret key agreement schemes: an amplify-and-forward (AF) scheme, a signal-combining amplify-and-forward (SC-AF) scheme, and a multiple-access amplify-and-forward (MA-AF) scheme. The key idea of these schemes is that each terminal shares the fading coefficients between all terminals and the relay, and use them as the source of a secret key. The AF scheme is based on a conventional amplify-and-forward two-way relaying method, whereas in the SC-AF scheme and the MA-AF scheme, we apply the idea of analog network coding to secret key agreement. We analyze eavesdropping strategies and show that the AF scheme is not secure if the eavesdropper is located near the relay and can receive signals from the relay without multipath fading and noise. Simulation results show that the SC-AF and MA-AF schemes are effective.

We propose a new authentication and key establishment (AKE) protocol that can be applied to low-power PDAs in Public Wireless LANs (PWLANs), using two factor authentication and precomputation. This protocol provides mutual authentication, identity privacy, and half forward-secrecy. The computational complexity that the client must perform is just one symmetric key encryption and five hash functions during the runtime of the protocol.