8Security Enhancement in IoMT‑Assisted Smart Healthcare System Using the Machine Learning Approach
Jayalakshmi Sambandan1*, Bharanidharan Gurumurthy2 and Syed Jamalullah R.3
1Department of Master of Computer Applications, MEASI Institute of Information Technology, Royapettah, Chennai, India
2Department of BCA, The New College, Chennai, India
3Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India
Abstract
The Internet of Medical Things (IoMT) is an emerging area that offers numerous valuable benefits to patients and healthcare providers in the identification and management of various illnesses. Despite its advantages, security remains a concern. IoMT devices contain a vast amount of clinical data, including personal information such as names, addresses, and medical histories, making data privacy and security challenging to maintain. The IoMT is highly susceptible to security breaches due to inexperienced users’ weak security practices and the prevalence of various intermediate attacks that may compromise sensitive medical data. To address these concerns, we propose utilizing the support vector machine with multilayer particle swarm optimization (SVM-MPSO) to enhance the IoMT data security. In the experimental analysis, the suggested techniques outperform the current system. The proposed method can be evaluated using a variety of criteria, including accuracy, precision, security, and sensitivity. The findings demonstrate ...
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