Abstract
Cognitive learning is progressively prospering in the field of Internet of Things (IoT). With the advancement in IoT, data generation rate has also increased, whereas issues like performance, attacks on the data, security of the data, and inadequate data resources are yet to be resolved. Recent studies are mostly focusing on the security of the data which can be handled by blockchain. Blockchain technology records the learned data into the block which is generated after completing proper consensus mechanism. In this paper, Hetero Federated Learning approach is used to apply cognitive learning on data produced by Internet of Thing devices. Security on cognitiveIoT data is provided by blockchain using Proof of Work consensus mechanism. By applying blockchain over heteroFL approach, we have conducted various simulations to check the performance of our proposed framework. Parameters taken into consideration during performance evaluation are effect of number of blocks on memory utilization and impact of data sample size on accuracy according to different learning rates.
Highlights
Previous Google chief director, Eric Schmidt made this striking IoT forecast: “ e Internet will vanish. ere will be numerous IP addresses, such countless gadgets, sensors, things that you are wearing, things that you are cooperating with, that you will not detect it
In-numerable efforts have been done from academia community, network providers, service providers, and various standard developing organizations, to provoke the growth of IoT devices [1]
Due to limited research carried out for security of IoT data produced by heterogeneous clients using HeteroFL, the research in this area is in its infancy. erefore, this paper focusses on providing security to heteroFL-based cognitive learned data using blockchain
Summary
Previous Google chief director, Eric Schmidt made this striking IoT forecast: “ e Internet will vanish. ere will be numerous IP addresses, such countless gadgets, sensors, things that you are wearing, things that you are cooperating with, that you will not detect it. In-numerable efforts have been done from academia community, network providers, service providers, and various standard developing organizations, to provoke the growth of IoT devices [1]. Most focused areas of research include networking, security, computations, communication, and energy harvesting but without cognitive ability, i.e., without brain, IoT seems awkward [2]. CIoT assists in bringing together physical world with the social world in an intelligent manner It includes smart learning, smart resource allocation, spectrum sensing, capturing high precision data, smart service provisioning, and information. Hetero Federated learning (HeteroFL) models are designed for devices that need different computation requirements and communication abilities. Cognitive computing is assisting a lot in making IoT become smarter by providing human intelligence to the systems. Cognitive computing is done by using heterogeneous federated learning to serve the needs of heterogeneous IoT clients.
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