Internet of Farming: Channel Characterization of Organic Communication Channels Internet of Farming (IoF) is the application of Internet of Things (IoT) to agriculture use cases. Organic channels are any hydrocarbon based media. When organic channels are used to communicate data, they are termed Organic Communication Channels (OCCs). The accomplishments of Human Body Communication (HBC) in Body Area Networks (BANs) suggests OCCsxe2x80x99 great potential when applied to cyberphysical systems. For example, soilbased and vegetationbased OCCs can be integrated into IoF scenarios. However other OCCs are less studied. This paper characterizes vegetationbased and soilbased OCCs through analysis of channel measurements and derivation of path loss equations. Presented results suggest logdistance path median path loss models hold for herbaceous vegetationbased channels. Furthermore, the results suggest vegetationbased channels were more frequencyselective than the soilbased channels examined.

A New RFPUF Based Authentication of Internet of Things Using Random Forest Classification This paper presents a novel RFPUF based authentication framework which exploits the intrinsic nonidealities in physical characteristic of a devicemedium to generate a unique identity for wireless nodes. It also takes the advantage of Random Forest classification to securely identify the sender nodes based on their unique features extracting from alreadyexisting modules in the receiver side. In contrast to the neural networkbased schemes, our proposed approach incurs lower design complexity and overheads, while it no longer needs a large amount of preparatory and preprocessing works related to the learning process and adjusting the network parameters. Thus, the overall runtime required to preparing and testing of network is drastically lessened. The experimental results show that the proposed scheme can reach to 100% accuracy in the identification of 225 nodes when a forest network with 100 trees and depth of 20 is developed, posing a negligible overhead on the receiver side. This high accuracy can be nearly achieved even in the presence of channel variations as our approach has less sensitivity to environmental conditions.