Survey of Distributed and Decentralized IoT Securities: Approaches Using Deep Learning and Blockchain Technology

Author:

Falayi Ayodeji1ORCID,Wang Qianlong1ORCID,Liao Weixian1ORCID,Yu Wei1

Affiliation:

1. Department of Computer and Information Sciences, Towson University, Towson, MD 21252, USA

Abstract

The Internet of Things (IoT) continues to attract attention in the context of computational resource growth. Various disciplines and fields have begun to employ IoT integration technologies in order to enable smart applications. The main difficulty in supporting industrial development in this scenario involves potential risk or malicious activities occurring in the network. However, there are tensions that are difficult to overcome at this stage in the development of IoT technology. In this situation, the future of security architecture development will involve enabling automatic and smart protection systems. Due to the vulnerability of current IoT devices, it is insufficient to ensure system security by implementing only traditional security tools such as encryption and access control. Deep learning and blockchain technology has now become crucial, as it provides distinct and secure approaches to IoT network security. The aim of this survey paper is to elaborate on the application of deep learning and blockchain technology in the IoT to ensure secure utility. We first provide an introduction to the IoT, deep learning, and blockchain technology, as well as a discussion of their respective security features. We then outline the main obstacles and problems of trusted IoT and how blockchain and deep learning may be able to help. Next, we present the future challenges in integrating deep learning and blockchain technology into the IoT. Finally, as a demonstration of the value of blockchain in establishing trust, we provide a comparison between conventional trust management methods and those based on blockchain.

Publisher

MDPI AG

Subject

Computer Networks and Communications

Reference142 articles.

1. Recent advancements and challenges of Internet of Things in smart agriculture: A survey;Sinha;Future Gener. Comput. Syst.,2022

2. Understanding the adoption of Industry 4.0 technologies in improving environmental sustainability;Javaid;Sustain. Oper. Comput.,2022

3. A systematic review of technologies and solutions to improve security and privacy protection of citizens in the smart city;Rizi;Internet Things,2022

4. A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications;Lin;IEEE Internet Things J.,2017

5. Malini, M., and Chandrakala, N. (2022). Evolutionary Computing and Mobile Sustainable Networks: Proceedings of ICECMSN 2021, Springer.

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Multichannel Image Encoding for Short Time-Series Feature Representation Applied to System Peak Demand Forecasting Model;2024 3rd International Conference on Computational Modelling, Simulation and Optimization (ICCMSO);2024-06-14

2. Numerical and analytical study of fractional order tumor model through modeling with treatment of chemotherapy;International Journal of Modelling and Simulation;2024-03-20

3. Integrating Smart Contracts in IoT Networks Powered by Blockchain Technology;2024 3rd International Conference for Innovation in Technology (INOCON);2024-03-01

4. Developing an IoT Adoption Framework for Library Management for Public Tertiary Institutions in Ghana;Advances in Library and Information Science;2024-01-26

5. W@rk: Attendance Application Framework Using Blockchain Technology;Lecture Notes on Data Engineering and Communications Technologies;2024

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3