Affiliation:
1. Research Center of Wuling Mountain Area, Characteristic Resources Development and Utilization, College of Finance and Economics, Yangtze Normal University, Chongqing 408100, P. R. China
2. School of Economics and Management, Chongqing Metropolitan College of Science and Technology, Chongqing 402167, P. R. China
3. Department of Computer Science and Engineering, Adhiyamaan College of Engineering, India
Abstract
Today, artificial intelligence (AI) can use the most powerful edge computing systems in the Internet of Things (IoT) for finding the information extracted from vast sensory data such as cyber effects or models in physical environments for classification, identification, and prediction. Heterogeneous IoT devices produce isolated and dispersed information parts, and knowledge sharing and exchange in IoT intelligent applications with several selfish nodes are necessary for complex tasks. In both academia and business, IoT is driving a digital revolution. However, protection and IoT privacy problems are challenged. It offers comfort for everyday lives. Blockchain, a shared cryptographic database, is a promising IoT encryption solution for several manufacturing, finance, and trade sectors. The IoT-based blockchain architecture is an interesting contrast to the conventional, centralized paradigm that struggles to fulfill specific IoT requirements. New concepts for applying data and resources management protection procedures in distributed networks and cloud computing are introduced. Cloud management services can be linked to the application through blockchain technology and distributed leader, a stable cognitive information system that facilitates management operations and securing data. This document provides many ideas for applying personal and behavioral characteristics to security and cryptography protocols, blockchain based on the cognitive cloud computing (BC-CCC) pattern. The simulation result shows that the proposed strategy can significantly enhance data transmission rate (96.2%), security ratio (94.5%), throughput ratio (92.4%), scalability ratio (91.5%), trust rate (93.8%), data trading ratio (96.2%), and reduce storage cost rate (25.1%) compared to other existing methods.
Funder
Chongqing Social Science Planning PhD Program
Humanities and Social Sciences Research Planning Project of Chongqing Education Commission in 2017
Science and Technology Research Program of Chongqing Municipal Education Commission
Publisher
World Scientific Pub Co Pte Ltd
Subject
Computer Science Applications,Modeling and Simulation
Cited by
9 articles.
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