在边缘计算中加强卸载和网络安全,实现数字孪生驱动的患者监护

IF 1.5 Q3 TELECOMMUNICATIONS
Ahmed K. Jameil, Hamed Al‐Raweshidy
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引用次数: 0

摘要

在医疗保健领域,数字孪生(DT)技术的使用被认为是通过实时远程监控加强病人护理的关键。然而,由于物联网(IoT)与远程医疗保健的结合,人们对风险预测、任务卸载和数据安全产生了担忧。本研究提出了一种新方法,将边缘计算与复杂的网络安全解决方案相结合。该系统收集了大量的环境和生理数据,可以全面了解患者的情况。该系统包括混合加密、威胁预测、梅克尔树验证、基于证书的身份验证和安全通信。通过使用 ESP32-Azure 物联网套件和 Azure 云来评估该提案的可行性,以评估该系统安全地向医疗机构和利益相关者发送患者数据的能力,同时维护数据的机密性。该系统的加密速度明显提高,效率提高了 27.18%,存储效率达到 0.673。此外,模拟结果表明,由于加密时间持续保持在较小的范围内,系统的性能并未受到加密的影响。此外,通过预测分析,还能发现可能存在的安全风险,并主动发出警报,从而有力地保证了数据完整性。结果表明,在改进的威胁预测下,所提出的系统通过物联网和云计算为受网络安全保护的 DT 医疗(DTH)高级建模和模拟提供了一种主动、个性化的护理方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing offloading with cybersecurity in edge computing for digital twin‐driven patient monitoring
In healthcare, the use of digital twin (DT) technology has been recognised as essential for enhancing patient care through real‐time remote monitoring. However, concerns regarding risk prediction, task offloading, and data security have been raised due to the integration of the Internet of Things (IoT) in remote healthcare. In this study, a new method was introduced, combines edge computing with sophisticated cybersecurity solutions. A vast amount of environmental and physiological data has been gathered, allowing for thorough understanding of patients. The system included hybrid encryption, threat prediction, Merkle Tree verification, certificate‐based authentication, and secure communication. The feasibility of the proposal was evaluated by using an ESP32‐Azure IoT Kit and Azure Cloud to evaluate the system's capacity to securely send patient data to healthcare institutions and stakeholders, while simultaneously upholding data confidentiality. The system demonstrated a notable improvement in encryption speed, with 27.18%, represented as the improved efficiency and achieved storage efficiency ratio 0.673. Furthermore, the evidence from the simulations showed that the system's performance was not affected by encryption since encryption times continuously remained within a narrow range. Moreover, proactive alert of probable security risks would be detected from the predictive analytics, hence strong data integrity assurance. The results suggest the proposed system provided a proactive, personalised care approach for cybersecurity‐protected DT healthcare (DTH) high‐level modelling and simulation, enabled via IoT and cloud computing under improved threat prediction.
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来源期刊
IET Wireless Sensor Systems
IET Wireless Sensor Systems TELECOMMUNICATIONS-
CiteScore
4.90
自引率
5.30%
发文量
13
审稿时长
33 weeks
期刊介绍: IET Wireless Sensor Systems is aimed at the growing field of wireless sensor networks and distributed systems, which has been expanding rapidly in recent years and is evolving into a multi-billion dollar industry. The Journal has been launched to give a platform to researchers and academics in the field and is intended to cover the research, engineering, technological developments, innovative deployment of distributed sensor and actuator systems. Topics covered include, but are not limited to theoretical developments of: Innovative Architectures for Smart Sensors;Nano Sensors and Actuators Unstructured Networking; Cooperative and Clustering Distributed Sensors; Data Fusion for Distributed Sensors; Distributed Intelligence in Distributed Sensors; Energy Harvesting for and Lifetime of Smart Sensors and Actuators; Cross-Layer Design and Layer Optimisation in Distributed Sensors; Security, Trust and Dependability of Distributed Sensors. The Journal also covers; Innovative Services and Applications for: Monitoring: Health, Traffic, Weather and Toxins; Surveillance: Target Tracking and Localization; Observation: Global Resources and Geological Activities (Earth, Forest, Mines, Underwater); Industrial Applications of Distributed Sensors in Green and Agile Manufacturing; Sensor and RFID Applications of the Internet-of-Things ("IoT"); Smart Metering; Machine-to-Machine Communications.
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