Guarding Digital Health: Deep Learning for Attack Detection in Medical IoT

Abstract

The Internet of Medical Things (IoMT) has transformed the healthcare sector by allowing for the continuous gathering, transfer, and analysis of medical data via networked devices.However, as IoMT has become more integrated into healthcare systems, it has been vulnerable to cybersecurity attacks, posing dangers to patient safety and data privacy. This study tackles the essential challenge of safeguarding the IoMT ecosystem by implementing cutting-edge deep learning approaches for threat identification and avoidance.Our study begins by looking at a variety of cyber risks that the IoMT faces, including as backdoors, DDoS assaults, MITM assaults, ransomware and SQL injections.These hostile operations may impair medical services and jeopardize critical med- ical data.To combat these risks, we offer a strong intrusion detection system, that constantly monitors the IoMT architecture for any unusual activity.The findings of this research contribute significantly to the development of a secure and resilient medical IoT ecosystem.The performance metrics of the proposed intrusion detection system, including accuracy, precision, recall, and F1 Score, were evaluated for four different models: CNN, Autoencoder, Transformer Network, and LSTM Network.The LSTM Network ex- hibited exceptional performance, achieving an accuracy of 97%, precision of 93%, recall of 96%, and an F1 Score of 94%.The compiled model, named Adam-LSTM, leverages the strengths of the Adam optimizer and LSTM architecture. Comparative anal- ysis with alternative algorithms demonstrated the superiority of the proposed approach in accurately and efficiently identifying intrusions.The IoMT can supply dependable healthcare services to patients while preserving their sensitive medical information by proactively securing digital health through deep learning-based threat detection.This study provides the groundwork for future breakthroughs in medical IoT cybersecurity solutions and promotes the idea of a smarter and safer healthcare landscape.