Leveraging Deep Learning for IoT Transceiver Identification.

With the increasing demand for Internet of Things (IoT) network applications, the lack of adequate identification and authentication has become a significant security concern. Radio frequency fingerprinting techniques, which utilize regular radio traffic as the identification source, were then proposed to provide a more secured identification approach compared to traditional security methods. Such solutions take hardware-level characteristics as device fingerprints to mitigate the risk of pre-shared key leakage and lower computational complexity. However, the existing studies suffer from problems such as location dependence. In this study, we have proposed a novel scheme for further exploiting the spectrogram and the carrier frequency offset (CFO) as identification sources. A convolutional neural network (CNN) is chosen as the classifier. The scheme addressed the location-dependence problem in the existing identification schemes. Experimental evaluations with data collected in the real world have indicated that the proposed approach can achieve 80% accuracy even if the training and testing data are collected on different days and at different locations, which is 13% higher than state-of-the-art approaches.

Electrochemical deposition of flower-like nanostructured silver particles with a PVA modified carbon cloth cathode.

A novel electrochemical method for preparing flower-like nanostructured silver particles using polyvinyl alcohol (PVA) modified carbon cloth as a cathode is reported. The method does not involve the use of any morphological control agents in aqueous solution. The morphology of the silver nanoparticles obtained was studied using scanning electron microscopy (SEM) and X-ray diffractometry (XRD). The effects of the operating conditions on the deposited silver nanoparticles were investigated. It was found that PVA concentration for carbon cloth modification had a significant effect on the deposited silver morphology. With 1% PVA modification, current density of 10 µA cm-2 and silver nitrate concentration of 1 mM, a flower-like nanostructured silver with petal thickness of 100 nm can be prepared. With the reaction proceeding, silver nanocrystals nucleated on the cathode in a few seconds, then the nuclei grew and the rudimental flower-like silver started to form in 1 min. The perfect flower-like nanostructure of silver was formed in 20 min. However overlong reaction time led to micrometer sized blocks. The specific silver nanostructure growth might be attributed to the silver ion concentration gradient caused by reaction and diffusion rate and the effects of PVA.