Unmanned Aerial Vehicle (UAV) plays a paramount role in various fields, such as military, aerospace, reconnaissance, agriculture, and many more. The development and implementation of these devices have become vital in terms of usability and reachability. Unfortunately, as they become widespread and their demand grows, they are becoming more and more vulnerable to several security attacks, including, but not limited to, jamming, information leakage, and spoofing. In order to cope with such attacks and security threats, a proper design of robust security protocols is indispensable. Although several pieces of research have been carried out with this regard, there are still research gaps, particularly concerning UAV-to-UAV secure communication, support for perfect forward secrecy, and provision of non-repudiation. Especially in a military scenario, it is essential to solve these gaps. In this paper, we studied the security prerequisites of the UAV communication protocol, specifically in the military setting. More importantly, a security protocol (with two sub-protocols), that serves in securing the communication between UAVs, and between a UAV and a Ground Control Station, is proposed. This protocol, apart from the common security requirements, achieves perfect forward secrecy and non-repudiation, which are essential to a secure military communication. The proposed protocol is formally and thoroughly verified by using the BAN-logic (Burrow-Abadi-Needham logic) and Scyther tool, followed by performance evaluation and implementation of the protocol on a real UAV. From the security and performance evaluation, it is indicated that the proposed protocol is superior compared to other related protocols while meeting confidentiality, integrity, mutual authentication, non-repudiation, perfect forward secrecy, perfect backward secrecy, response to DoS (Denial of Service) attacks, man-in-the-middle protection, and D2D (Drone-to-Drone) security.

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5G has introduced various emerging demands for new services and technologies that raised the bar for quality of service, latency, handovers, and data rates. Such diverse and perplexing network requirements bring numerous issues, among which security stands in the first row. The backhaul, which can be implemented as a wired or wireless solution, serves as a bridge between the radio access and core networks assuring connectivity to end users. The recent trends in backhaul usage rely on wireless technologies implemented using point-to-point (PTP) or point-to-multipoint (P2MP) configurations. Unfortunately, due to the nature of the transmission medium, the wireless backhaul is vulnerable and exposed to more various security threats and attacks than the wired one. In order to protect the backhaul, there have been several researches, whose authentication and key exchange scheme mainly depends on the existing security standards such as transport layer security (TLS), Internet Key Exchange version 1 (IKEv1), IKEv2, Host Identity Protocol (HIP), and Authentication and Key Agreement (AKA). However, such security standards cannot completely fulfil the security requirements including security policy update, key update, and balancing between security and efficiency, which are necessary for the emerging 5G networks. This is basically the motive behind why we study and propose a new security protocol for the backhaul link of wireless access network based on P2MP model. The proposed protocol is designed to be 5G-aware, and provides mutual authentication, perfect forward secrecy, confidentiality, integrity, secure key exchange, security policy update, key update, and balancing trade-off between efficiency and security while preventing resource exhaustion attacks. The protocol's correctness is formally verified by the well-known formal security analysis tools: BAN-logic and Scyther. Moreover, the derived lemmas prove that the security requirements are satisfied. Finally, from a comparison analysis, it is shown that the proposed protocol is better than other standard protocols.

The Internet of Medical Things (IoMT) has risen to prominence as a possible backbone in the health sector, with the ability to improve quality of life by broadening user experience while enabling crucial solutions such as near real-time remote diagnostics. However, privacy and security problems remain largely unresolved in the safety area. Various rule-based methods have been considered to recognize aberrant behaviors in IoMT and have demonstrated high accuracy of misbehavior detection appropriate for lightweight IoT devices. However, most of these solutions have privacy concerns, especially when giving context during misbehavior analysis. Moreover, falsified or modified context generates a high percentage of false positives and, in some cases, causes a by-pass in misbehavior detection. Relying on the recent powerful consolidation of Blockchain and federated learning (FL), we propose an efficient privacy-preserving framework for secure misbehavior detection in lightweight IoMT devices, particularly in the artificial pancreas system (APS). The proposed approach employs privacy-preserving bidirectional long-short term memory (BiLSTM) and augments the security through the integration of Blockchain technology based on Ethereum smart contract environment. Furthermore, the effectiveness of the proposed model is benchmarked empirically in terms of sustainable privacy preservation, commensurate incentive scheme with an untraceability feature, exhaustiveness, and the compact results of a variant neural network approach. As a result, the proposed model has a 99.93% recall rate, showing that it can detect virtually all possible malicious events in the targeted use case. Furthermore, given an initial ether value of 100, the solution's average gas consumption and Ether spent are 84,456.5 and 0.03157625, respectively.