Optimized Fuzzy Secure Scheme for Trust Assessment in IoMT

Rapid development of technologies associated with the Internet of Medical Things (IoMT) has enabled continuous patient monitoring, diagnosis, and integration of medical devices with various healthcare infrastructures. However, the increasing heterogeneity of IoMT systems and their connectivity-related features introduce also security risks, such as data tampering, unauthorized access, and unsafe behavior of the devices themselves. Traditional trust assessment techniques often fail to handle the uncertainty inherent in medical data and devices. This paper presents a fuzzy logic-based secure trust assessment scheme designed for IoMT, which integrates behavioral and communication indicators to compute trust scores for a device. The scheme employs a fuzzy logic-based approach and provides a trust level evaluation procedure suitable for resource-limited IoMT devices. A fuzzy inference system was developed specifically for this scheme and further optimized by applying evolutionary algorithms. The experimental results demonstrate an improved accuracy of the optimized model in evaluating the trust level of devices and show its enhanced accuracy compared to a classical trust mechanism.