An Intelligent and Trust‐Enabled Farming Systems With Blockchain and Digital Twins on Mobile Edge Computing

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Network Management Pub Date : 2024-08-22 DOI:10.1002/nem.2299
Geetanjali Rathee, Hemraj Saini, Selvaraj Praveen Chakkravarthy, Rajagopal Maheswar
{"title":"An Intelligent and Trust‐Enabled Farming Systems With Blockchain and Digital Twins on Mobile Edge Computing","authors":"Geetanjali Rathee, Hemraj Saini, Selvaraj Praveen Chakkravarthy, Rajagopal Maheswar","doi":"10.1002/nem.2299","DOIUrl":null,"url":null,"abstract":"Advancement and flourishment in mobile edge computing (MEC) have motivated the farmers to deploy an efficient ecosystem in their farms. For further real‐time monitoring and surveillance of the environment along with the deployment of intelligent farming, digital twin is considered as one of the emerging and most promising technologies. For proper optimization and utilization of physical systems, the physical components of the ecosystems are connected with the digital space. Further, the smart technologies and devices have convinced to address the expected level of requirements for accessing the rapid growth in farming associated with digital twins. However, with a large number of smart devices, huge amount of generated information from heterogeneous devices may increase the privacy and security concern by challenging the interrupting operations and management of services in smart farming. In addition, the growing risks associated with MEC by modifying the sensor readings and quality of service further affect the overall growth of intelligent farming. In order to resolve these challenges, this paper has proposed a secure surveillance architecture to detect deviations by incorporating digital twins in the ecosystem. Further, for real‐time monitoring and preprocessing of information, we have integrated a four‐dimensional trust mechanism along with blockchain. The four‐dimensional trusted method recognizes the behavior of each communicating device during the transmission of information in the network. Further, blockchain strengthens the surveillance process of each device behavior by continuously monitoring their activities. The proposed mechanism is tested and verified against various abnormalities received from sensors by simulating false use cases in the ecosystem and compared against various security metrics over existing approaches. Furthermore, the proposed mechanism is validated against several security threats such as control command threat, coordinated cyber threats, accuracy, and decision‐making and prediction of records over existing methods.","PeriodicalId":14154,"journal":{"name":"International Journal of Network Management","volume":"16 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Network Management","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1002/nem.2299","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Advancement and flourishment in mobile edge computing (MEC) have motivated the farmers to deploy an efficient ecosystem in their farms. For further real‐time monitoring and surveillance of the environment along with the deployment of intelligent farming, digital twin is considered as one of the emerging and most promising technologies. For proper optimization and utilization of physical systems, the physical components of the ecosystems are connected with the digital space. Further, the smart technologies and devices have convinced to address the expected level of requirements for accessing the rapid growth in farming associated with digital twins. However, with a large number of smart devices, huge amount of generated information from heterogeneous devices may increase the privacy and security concern by challenging the interrupting operations and management of services in smart farming. In addition, the growing risks associated with MEC by modifying the sensor readings and quality of service further affect the overall growth of intelligent farming. In order to resolve these challenges, this paper has proposed a secure surveillance architecture to detect deviations by incorporating digital twins in the ecosystem. Further, for real‐time monitoring and preprocessing of information, we have integrated a four‐dimensional trust mechanism along with blockchain. The four‐dimensional trusted method recognizes the behavior of each communicating device during the transmission of information in the network. Further, blockchain strengthens the surveillance process of each device behavior by continuously monitoring their activities. The proposed mechanism is tested and verified against various abnormalities received from sensors by simulating false use cases in the ecosystem and compared against various security metrics over existing approaches. Furthermore, the proposed mechanism is validated against several security threats such as control command threat, coordinated cyber threats, accuracy, and decision‐making and prediction of records over existing methods.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
移动边缘计算上的区块链和数字双胞胎智能化、可信任的农业系统
移动边缘计算(MEC)的进步和蓬勃发展促使农民在农场中部署高效的生态系统。为了进一步对环境进行实时监测和监控,同时部署智能农业,数字孪生被认为是最有前途的新兴技术之一。为了适当优化和利用物理系统,生态系统的物理组件与数字空间相连接。此外,智能技术和设备已确信能够满足与数字孪生相关的农业快速增长的预期要求。然而,随着智能设备的大量出现,来自异构设备的海量信息可能会增加隐私和安全问题,对智能农业服务的中断操作和管理构成挑战。此外,通过修改传感器读数和服务质量而与 MEC 相关的风险不断增加,进一步影响了智能农业的整体发展。为了解决这些挑战,本文提出了一种安全监控架构,通过将数字双胞胎纳入生态系统来检测偏差。此外,为了实现实时监控和信息预处理,我们将四维信任机制与区块链结合在一起。四维信任方法可识别网络信息传输过程中每个通信设备的行为。此外,区块链通过持续监控每个设备的活动,加强了对其行为的监控过程。通过模拟生态系统中的虚假用例,针对从传感器接收到的各种异常情况对所提出的机制进行了测试和验证,并与现有方法的各种安全指标进行了比较。此外,与现有方法相比,还针对控制指令威胁、协同网络威胁、准确性、决策和记录预测等几种安全威胁对所提出的机制进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
International Journal of Network Management
International Journal of Network Management COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS
CiteScore
5.10
自引率
6.70%
发文量
25
审稿时长
>12 weeks
期刊介绍: Modern computer networks and communication systems are increasing in size, scope, and heterogeneity. The promise of a single end-to-end technology has not been realized and likely never will occur. The decreasing cost of bandwidth is increasing the possible applications of computer networks and communication systems to entirely new domains. Problems in integrating heterogeneous wired and wireless technologies, ensuring security and quality of service, and reliably operating large-scale systems including the inclusion of cloud computing have all emerged as important topics. The one constant is the need for network management. Challenges in network management have never been greater than they are today. The International Journal of Network Management is the forum for researchers, developers, and practitioners in network management to present their work to an international audience. The journal is dedicated to the dissemination of information, which will enable improved management, operation, and maintenance of computer networks and communication systems. The journal is peer reviewed and publishes original papers (both theoretical and experimental) by leading researchers, practitioners, and consultants from universities, research laboratories, and companies around the world. Issues with thematic or guest-edited special topics typically occur several times per year. Topic areas for the journal are largely defined by the taxonomy for network and service management developed by IFIP WG6.6, together with IEEE-CNOM, the IRTF-NMRG and the Emanics Network of Excellence.
期刊最新文献
Issue Information Security, Privacy, and Trust Management on Decentralized Systems and Networks A Blockchain-Based Proxy Re-Encryption Scheme With Cryptographic Reverse Firewall for IoV Construction of Metaphorical Maps of Cyberspace Resources Based on Point-Cluster Feature Generalization Risk-Aware SDN Defense Framework Against Anti-Honeypot Attacks Using Safe Reinforcement Learning
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1