Securing IoT-Based Healthcare Systems Against Malicious and Benign Congestion

The Internet of Things (IoT) has made it possible to gather patient data through a network of sensors, referred to as the wireless body area network (WBAN). However, the variability of the wireless channels can pose a challenge to the real-time functionality of Medical IoT (MIoT) systems. These delays can occur due to either natural or malicious congestion in the wireless channels. To address this issue, we present an efficient algorithm that partitions the WBAN nodes within an MIoT system to balance the traffic load across the entire system. In our model, each network partition includes an access point (AP) responsible for managing all the WBANs within its coverage range. Our proposed algorithm enables the APs to dynamically readjust their coverage range based on the overall traffic load, thereby evenly distributing the load among APs to alleviate congested areas. Moreover, the APs continuously monitor the traffic to detect and mitigate congested areas, regardless of whether the congestion is due to a natural load or a malicious traffic injection attack. Based on the simulations done using NS2, the proposed algorithm: 1) can resolve congestion of both cases very efficiently; 2) improves the network delay variation by at least 40%; and 3) improves the network energy consumption and network delay by at least 30% and 44%, respectively.