Review on Open-Source IoT and Edge-Compatible Devices for Health Monitoring Applications

As the Internet of Things (IoT) grows in popularity, devices in healthcare, novel solutions for remote patient monitoring and health management have become possible.This increasing interconnectedness, however, raises substantial cybersecurity threats.The goal of this research is to discuss the detection and prevention of cyber-attacks in an IoT-based health monitoring application.To safeguard the IoT ecosystem, the suggested method takes a multi-layered approach.Device authentication and access control procedures are used to guarantee that only authorized devices can connect to the network.This stops bad actors from gaining access to the system through illegal entry points.To identify aberrant activities and possible cyber-attacks, anomaly detection methods are used.Machine learning algorithms evaluate IoT device data to build baseline patterns of typical activity.Deviations from these patterns generate alarms, allowing for immediate analysis and intervention.To protect the transfer of sensitive health data between devices and the backend infrastructure, secure communication methods are used.Data interception and unwanted access are reduced via encryption methods and secure connections.