一个基于物联网的医疗保健系统,使用区块链技术和多规模堆叠的Residual-GRU来安全传输数据
Anguraju Krishnan1, Rajesh Arunachalam2, S N V J Devi Kosuru3
1Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Thandalam, Chennai, 602105, Tamil Nadu, India.
Scientific reports
|December 30, 2025
概括
这项研究介绍了使用区块链和先进的人工智能来检测攻击的物联网医疗数据的安全系统. 它实现了96.22%的准确性,增强了患者数据隐私和系统安全.
科学领域:
- 网络安全 网络安全
- 人工智能的人工智能
- 医疗保健技术 技术 医疗保健 技术
背景情况:
- 医疗保健中的物联网 (IoT) 设备传输敏感的患者数据,使他们容易受到网络攻击和漏洞.
- 现有的安全措施往往无法在支持物联网的医疗保健系统中提供对复杂威胁的全面保护.
- 确保数据完整性,隐私和安全传输对于值得信赖的医疗保健应用程序至关重要.
研究的目的:
- 为物联网辅助医疗设备开发一种新的,安全的数据传输系统.
- 加强网络攻击的检测,并确保患者数据的保密性.
- 将区块链技术与先进的机器学习相结合,以实现强大的安全性和透明度.
主要方法:
- 一个集成区块链的系统,用于特征提取的多目标加权受限制的博尔兹曼机器 (MW-RBM),用于重量优化的基于放大养的美国斑马优化 (MFAZO) 和用于攻击检测的多尺度堆叠残余门反复单元 (MSRes-GRU).
- 使用同型多项式加密 (HPE) 来保护医疗保健数据在传输过程中.
- 雇佣了MFAZO来优化MW-RBM重量,改善特征提取和攻击检测准确度.
主要成果:
- 拟议的MSRes-GRU模型实现了96.22%的高检测精度.
- 这种精度明显优于传统模型,如DNN (85.65%),LSTM (80.71%),SVM (89.99%) 和GRU (94.14%).
- 该系统在识别基于物联网的攻击方面表现强,同时通过区块链确保安全和透明的数据传输.
结论:
- MSRes-GRU和区块链的新组合为支持物联网的医疗数据传输提供了一个安全,透明和可扩展的解决方案.
- 优化的功能提取和先进的攻击检测显著提高了数据安全性和隐私.
- 这项研究为可信的医疗保健应用提供了一个可靠的模型,保护患者数据的完整性.
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