使用区块链和迁移学习技术确保物联网数据传播安全。

IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Pooja Anand, Yashwant Singh, Harvinder Singh
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引用次数: 0

摘要

在智能应用中,物联网数据流对于建立对可持续物联网解决方案的信任至关重要。然而,大多数用于存储和传播物联网数据流的现有系统缺乏可靠性、安全性和透明度,主要原因是集中式架构会造成单点故障。为了解决这些限制,本研究引入了TraVel,这是一种基于区块链和迁移学习的安全物联网数据管理框架。TraVel利用分散的IPFS存储有效地处理大量数据,并与私有以太坊区块链集成,以增强数据完整性和可访问性。在提出的方案中,智能家居([公式:见文本])数据被安全地收集并通过BC访问,并在IPFS上为所有文件生成唯一的哈希密钥。自动执行的以太坊智能合约执行访问控制并验证数据完整性,只允许存储经过验证的非恶意数据。采用对抗域自适应(DA)学习模型,在恶意数据进入区块链之前对其进行检测和过滤。TraVel的性能在区块链参数上进行了评估,并在REMIX IDE和星际文件系统(IPFS)上进行了模拟,展示了其在安全物联网数据传播方面的可靠性和可扩展性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Secure IoT data dissemination with blockchain and transfer learning techniques.

In smart applications, streaming IoT data is essential to building trust in sustainable IoT solutions. However, most existing systems for storing and disseminating IoT data streams lack reliability, security, and transparency, primarily due to centralized architectures that create single points of failure. To address these limitations, this research introduces TraVel, a blockchain and transfer learning-based framework for secure IoT data management. TraVel leverages decentralized IPFS storage to handle large data volumes effectively, integrating with a private Ethereum blockchain to enhance data integrity and accessibility. In the proposed scheme, the smart home ([Formula: see text]) data is collected securely and accessed over the BC with a unique hash key generated on the IPFS for all the files. Self-executing Ethereum smart contracts enforce access control and verify data integrity, allowing only validated, non-malicious data to be stored. An adversarial domain adaptation (DA) learning model is employed to detect and filter malicious data before it enters the blockchain. TraVel's performance is evaluated on blockchain parameters, with simulations conducted on REMIX IDE and InterPlanetary File System (IPFS), demonstrating its reliability and scalability for secure IoT data dissemination.

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来源期刊
Scientific Reports
Scientific Reports Natural Science Disciplines-
CiteScore
7.50
自引率
4.30%
发文量
19567
审稿时长
3.9 months
期刊介绍: We publish original research from all areas of the natural sciences, psychology, medicine and engineering. You can learn more about what we publish by browsing our specific scientific subject areas below or explore Scientific Reports by browsing all articles and collections. Scientific Reports has a 2-year impact factor: 4.380 (2021), and is the 6th most-cited journal in the world, with more than 540,000 citations in 2020 (Clarivate Analytics, 2021). •Engineering Engineering covers all aspects of engineering, technology, and applied science. It plays a crucial role in the development of technologies to address some of the world''s biggest challenges, helping to save lives and improve the way we live. •Physical sciences Physical sciences are those academic disciplines that aim to uncover the underlying laws of nature — often written in the language of mathematics. It is a collective term for areas of study including astronomy, chemistry, materials science and physics. •Earth and environmental sciences Earth and environmental sciences cover all aspects of Earth and planetary science and broadly encompass solid Earth processes, surface and atmospheric dynamics, Earth system history, climate and climate change, marine and freshwater systems, and ecology. It also considers the interactions between humans and these systems. •Biological sciences Biological sciences encompass all the divisions of natural sciences examining various aspects of vital processes. The concept includes anatomy, physiology, cell biology, biochemistry and biophysics, and covers all organisms from microorganisms, animals to plants. •Health sciences The health sciences study health, disease and healthcare. This field of study aims to develop knowledge, interventions and technology for use in healthcare to improve the treatment of patients.
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