On the one hand, the Internet of Medical Things (IoMT) in healthcare systems has emerged as a promising technology to monitor patients’ health and provide reliable medical services, especially in remote and underserved areas. On the other hand, in disaster scenarios, the loss of communication infrastructure can make it challenging to establish reliable communication and to provide timely first aid services. To address this challenge, unmanned aerial vehicles (UAVs) have been adopted to assist hospital centers in delivering medical care to hard-to-reach areas. Despite the potential of UAVs to improve medical services in emergency scenarios, their limited resources make their security critical. Therefore, developing secure and efficient communication protocols for IoMT networks using UAVs is a vital research area that can help ensure reliable and timely medical services. In this paper, we introduce a novel Stackelberg security-based game theory algorithm, named Stackelberg ad hoc on-demand distance vector (SBAODV), to detect and recover data affected by black hole attacks in IoMT networks using UAVs. Our proposed scheme utilizes the substantial Stackelberg equilibrium (SSE) to formulate strategies that protect the system against attacks. We evaluate the performance of our proposed SBAODV scheme and compare it with existing routing schemes. Our results demonstrate that our proposed scheme outperforms existing schemes regarding packet delivery ratio (PDR), networking load, throughput, detection ratio, and end-to-end delay. Specifically, our proposed SBAODV protocol achieves a PDR of 97%, throughput ranging from 77.7 kbps to 87.3 kbps, and up to 95% malicious detection rate at the highest number of nodes. Furthermore, our proposed SBADOV scheme offers significantly lower networking load (7% to 30%) and end-to-end delay (up to 30%) compared to existing routing schemes. These results demonstrate the efficiency and effectiveness of our proposed scheme in ensuring reliable and secure communication in IoMT emergency scenarios using UAVs.

A voltage stability index is proposed using a new single-port equivalent depending on component peculiarity representation and sensitivity persistence to locate and determine long-term voltage instability in transmission and distribution power networks. The suggested single-port equivalent effectively represents the equivalence of various component types and assures the consistency of sensitivity information before and after the equivalence which is compulsory for the equivalent accuracy in estimating the voltage stability analysis. The stability index is derived from the new single-port equivalent to determine the system voltage instability. The proposed stability index is compared with indices based on virtual impedance and Thevenin impedance models. This new stability index shows more accuracy and effectiveness as compared to the indices based on virtual and Thevenin equivalent models. The index also determines the weak buses, where an improvement or functional measure can be used to reduce the system voltage instability. The validity of the proposed equivalent approach and stability index is presented by utilizing two radial systems, four IEEE systems and an actual system having bus size from five to 1010 buses.