Blockchain-Enabled Intrusion Detection for Medical IoT Devices: A Privacy-Preserving Security Framework

Abstract

In modern health care infrastructure the internet of medical things (IoMt) is become a backbone due to devices have resource limitation of risks which consider the security design for the future.  We have introduce the farmwork which instruct the detection with blockchain technology with privacy that preserve the leaning to secure the deployments of cross site IoMT. Our aim to target in current system to target three critical weakness: the in centralized cloud monitor the single point of failure that’s inherited, the low power devices have bottlenecks communication and the de to challenges of maintain privacy of patients due to threat detection in collaboration.  To validate our system we have use the comprehensive CIC IoMT 2024 benchmark dataset, using various protocols on 40 different medical devices to capture real world traffic. We achieved a 99% accuracy rate in detecting attacks by applying an ensemble classifier to a dimensionality-reduced feature set. In addition we have knoswledge distillation for cutting the communication inter hospital  87%  without guarantees of formal privacy . To cover the evaluation of five classes include spoofing, DDoS and access that unauthorized along to demonstration of thins frame work is viable for the deployment of the real world on edge gateway and resource constrain wearable , this enable the institution for collaborate securely without data which is centralized sensitive.