Blockchain and Reinforcement Neural Network for Trusted Cloud-Enabled IoT Network

被引:5
|
作者
Samriya, Jitendra Kumar [1 ]
Kumar, Surendra [2 ]
Kumar, Mohit [3 ]
Xu, Minxian [4 ]
Wu, Huaming [5 ]
Gill, Sukhpal Singh [6 ]
机构
[1] Indian Inst Informat Technol Sonepat, Dept CSE, Sonepat 131001, India
[2] GLA Univ, Dept Comp Engn & Applicat, Mathura 281406, India
[3] Dr BR Ambedkar Natl Inst Technol, Dept IT, Jalandhar 144011, India
[4] Shenzhen Inst Adv Technol, Chinese Acad Sci, Shenzhen 518055, Peoples R China
[5] Tianjin Univ, Ctr Appl Math, Tianjin 300072, Peoples R China
[6] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London E1 4NS, England
基金
中国国家自然科学基金;
关键词
Internet of Things; Cloud computing; Blockchains; Security; 5G mobile communication; Network security; Computer architecture; reinforcement neural network; heterogeneous autonomous network; cloud computing; control system; SOFTWARE-DEFINED NETWORKING; 5G; INTERNET;
D O I
10.1109/TCE.2023.3347690
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The rapid integration of Internet of Things (IoT) services and applications across various sectors is primarily driven by their ability to process real-time data and create intelligent environments through artificial intelligence for service consumers. However, the security and privacy of data have emerged as significant threats to consumers within IoT networks. Issues such as node tampering, phishing attacks, malicious code injection, malware threats, and the potential for Denial of Service (DoS) attacks pose serious risks to the safety and confidentiality of information. To solve this problem, we propose an integrated autonomous IoT network within a cloud architecture, employing Blockchain technology to heighten network security. The primary goal of this approach is to establish a Heterogeneous Autonomous Network (HAN), wherein data is processed and transmitted through cloud architecture. This network is integrated with a Reinforced Neural Network (RNN) called ClouD_RNN, specifically designed to classify the data perceived and collected by sensors. Further, the collected data is continuously monitored by an autonomous network and classified for fault detection and malicious activity. In addition, network security is enhanced by the Blockchain Adaptive Windowing Meta Optimization Protocol (BAW_MOP). Extensive experimental results validate that our proposed approach significantly outperforms state-of-the-art approaches in terms of throughput, accuracy, end-to-end delay, data delivery ratio, network security, and energy efficiency.
引用
收藏
页码:2311 / 2322
页数:12
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