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Automated detection of cybersecurity attacks in healthcare systems with recursive feature elimination and multilayer perceptron optimization

Firat Kilincer Ilhan, Ertam Fatih, Sengur Abdulkadir, Tan Ru-San, Rajendra Acharya U.

Biocybernetics and Biomedical Engineering

2023

Vol. 43, no. 1

30--41

Widespread proliferation of interconnected healthcare equipment, accompanying software, operating systems, and networks in the Internet of Medical Things (IoMT) raises the risk of security compromise as the bulk of IoMT devices are not built to withstand internet attacks. In this work, we have developed a cyber-attack and anomaly detection model based on recursive feature elimination (RFE) and multilayer perceptron (MLP). The RFE approach selected optimal features using logistic regression (LR) and extreme gradient boosting regression (XGBRegressor) kernel functions. MLP parameters were adjusted by using a hyperparameter optimization and 10-fold cross-validation approach was performed for performance evaluations. The developed model was performed on various IoMT cybersecurity datasets, and attained the best accuracy rates of 99.99%, 99.94%, 98.12%, and 96.2%, using Edith Cowan University- Internet of Health Things (ECU-IoHT), Intensive Care Unit (ICU Dataset), Telemetry data, Operating systems’ data, and Network data from the testbed IoT/IIoT network (TON-IoT), and Washington University in St. Louis enhanced healthcare monitoring system (WUSTL-EHMS) datasets, respectively. The proposed method has the ability to counter cyber attacks in healthcare applications.

The internet of medical things and artificial intelligence: trends, challenges, and opportunities

Kakhi Kourosh, Alizadehsani Roohallah, Kabir H. M. Dipu, Khosravi Abbas, Nahavandi Saeid, Acharya U. Rajendra

Biocybernetics and Biomedical Engineering

2022

Vol. 42, no. 3

749--771

High quality and efficient medical service is one of the major factors defining living standards. Developed countries strive to make their healthcare systems as efficient and cost-effective as possible. Remote medical services are a promising approach to lower medical costs and, at the same time, accelerating diagnosis and treatment of diseases. Internet of things (IoT) has the power to connect several devices, users, databases, etc., in a unified manner. Internet of medical things (IoMT) is some type of IoT designed to facilitate medical services. Using IoMT, many of the medical tasks, such as chronic disease monitoring, disease diagnosis, etc., can be realized remotely, leading to lower healthcare costs and better services. This paper is devoted to the role of artificial intelligence (AI) in recent advances on IoMT. Hardware requirements and recent articles proposing solutions for IoMTusing AI are reviewed. A comprehensive list of major benefits and challenges is presented as well. Wearable medical devices (WMDs) are also investigated. The WMDs classification is also performed based on their technology. Market share and its anticipated growth for different types of WMDs are also analyzed for the first time. Moreover, common applications of AI in IoMT are reviewed and then classified based on their usage. The paper is closed with the conclusion and possible directions for future works.