[This article belongs to Volume - 56, Issue - 02, 2024]
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-18-07-2024-04

Title : INTERNET-OF-THINGS ARCHITECTURE BASED ON BLOCKCHAIN TECHNOLOGY AND MACHINE LEARNING FOR SENSOR ACCESS CONTROL SYSTEMS FOR DATA SECURITY
Yogesh Chandrakant Khairnar, Nagesh Salimath

Abstract :

The Internet of Things (IoT) is a technology that connects billions of devices, or "things," to each other (machine-to-machine) and to people through existing infrastructure. Real-world IoT applications include smart cities, smart homes, connected appliances, shipping and monitoring systems, smart supply chain management, and smart grids. As the number of devices worldwide increases across all aspects of daily life, vast amounts of data are generated. This surge in data brings about new challenges related to the development and use of current technologies, particularly concerning new applications, regulation, cloud computing, security, and privacy. Blockchain technology has shown promise in securing and preserving user data privacy in a decentralized manner. Specifically, Hyperledger Fabric v2.x, an open-source blockchain platform, offers versatility, modularity, and high performance. In this paper, we present a blockchain as a service (BaaS) application based on Hyperledger Fabric to address the security and privacy challenges associated with IoT. We introduce a new architecture to facilitate this integration, which has been developed, deployed, and analysed in real-world scenarios. Additionally, we propose a new data structure with encryption based on public and private keys to enhance security and privacy.