SecureEdge-MedChain:一个后量子区块链和联合学习框架,用于IoMT中的实时预测诊断
Sivasubramanian Ravisankar1, Rajagopal Maheswar2
1Department of Computer Science and Engineering, Coimbatore Institute of Technology, Coimbatore 641 014, Tamil Nadu, India.
Sensors (Basel, Switzerland)
|October 16, 2025
概括
Med-Q Ledger通过区块链和后量子加密技术提高了医疗物联网 (IoMT) 的安全性和性能. 它可以实时进行隐私保护分析,用于关键应用,例如预测婴儿肠道并发症.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 医疗信息学 医疗信息学
背景情况:
- 医疗物联网 (IoMT) 面临着可扩展性,数据机密性对抗量子威胁以及实时隐私保护情报方面的挑战.
- 现有的IoMT系统难以满足高容量的数据处理和医疗保健中的强大安全性的需求.
研究的目的:
- 介绍Med-Q Ledger,这是一个新的框架,用于解决IoMT可扩展性,数据安全性和隐私方面的局限性.
- 通过安全高效的数据分析,增强实时患者监测和预测诊断.
主要方法:
- 集成了一个许可的Hyperledger Fabric与Holochain DHT,以实现可扩展性和交易完整性.
- 集成的后量子加密 (PQC) 使用Crystals-Di和Kyber密钥封装机制用于数据安全.
- 利用基于边缘的联合学习 (FL) 与自动编码器用于对加密梯度的隐私保护异常检测.
主要成果:
- 实现了高吞吐量 (~3400 TPS) 低延迟 (~180 ms) 和>95%的异常检测率.
- 在预测早产婴儿的结肠口术必要性方面表现卓越,F1得分为0.90.
- 与基线相比,报告了11%的PQC通用费用,25%的紧急手术减少,31%的能源消耗降低.
结论:
- Med-Q Ledger为IoMT分析提供了一个安全,可扩展和保护隐私的框架.
- 该框架为下一代医疗保健部署设定了新的基准,改善了患者的治疗结果和运营效率.
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