MR-TBA – An improved Trust-based Security mechanism for IoT Networks

IoT has transformed healthcare by enabling remote patient monitoring, resource management, and personalized therapies. The integration of many networked devices has prompted data security and privacy concerns. This paper examines healthcare IoT security measures that protect patient data. Encryption, access control, authentication, and intrusion detection are common methods. These approaches provide significant safety, but they typically fail to address healthcare IoT's growing threats and complex network environments. This work examines how trust-based security paradigms reduce healthcare IoT risks. Reputation systems, behavior analysis, and trust models create dynamic and adaptive security. These methods improve threat detection and response by assessing network devices and entities' trustworthiness, reducing the risk of unwanted access and data breaches. Trust-based security solutions outperform traditional security methods in resilience to sophisticated attacks and adaptability to changing threat landscapes. Results show that trust-based security models increase anomaly detection, false positive reduction, and healthcare IoT trust and integrity.