Today, intelligent drone technology is rapidly expanding, particularly in the defense industry. A swarm of drones can communicate, share data, and make the best decisions on their own. Drone swarms can swiftly and effectively carry out missions like surveillance, reconnaissance, and rescue operations, without exposing military troops to hostile conditions. However, there are still significant problems that need to be resolved. One of them is to protect communications on these systems from threat actors. In this paper, we use blockchain technology as a defense mechanism against such issues. Drones can communicate data safely, without the need for a centralized authority (ground station), when using a blockchain to facilitate communication between them in a leader–follower hierarchy structure. Solidity has been used to create a compact, lightweight, and effective smart contract that automates the process of choosing a position in a certain swarm formation structure. Additionally, a mechanism for electing a new leader is proposed. The effectiveness of the presented model is assessed through a simulation that makes use of a DApp we created and Gazebo software. The purpose of this work is to develop a reliable and secure UAV swarm communication system that will enable widespread global adoption by numerous sectors.

UAVs are increasingly being used in various domains, from personal and commercial applications to military operations. Ensuring the security and trustworthiness of UAV communications is crucial, and blockchain technology has been explored as a solution. However, privacy remains a challenge, especially in public blockchains. In this work, we propose a novel approach utilizing zero-knowledge proof techniques, specifically zk-SNARKs, which are non-interactive cryptographic proofs. This approach allows UAVs to prove their authenticity or location without disclosing sensitive information. We generated zk-SNARK proofs using the Zokrates tool on a Raspberry Pi, simulating a drone environment, and analyzed power consumption and CPU utilization. The results are promising, especially in the case of larger drones with higher battery capacities. Ethereum was chosen as the public blockchain platform, with smart contracts developed in Solidity and tested on the Sepolia testnet using Remix IDE. This novel proposed approach paves the way for a new path of research in the UAV area.

In this paper, we introduce the Levy Flight-enhanced Whale Optimization Algorithm with Tabu Search elements (LWOATS), an innovative hybrid optimization approach that enhances the standard Whale Optimization Algorithm (WOA) with advanced local search techniques and elite solution management to improve performance on global optimization problems. Techniques from the Tabu Search algorithm are adopted to balance the exploration and exploitation phases, while an elite reintroduction strategy is implemented to retain and refine the best solutions. The efficient optimization of LWOATS is further aided by the utilization of Levy flights and local search based on the Nelder–Mead simplex method. An Orthogonal Experimental Design (OED) analysis was employed to fine-tune the algorithm’s parameters. LWOATS was tested against three different algorithm sets: fundamental algorithms, advanced Differential Evolution (DE) variants, and improved WOA variants. Wilcoxon tests demonstrate the promising performance of LWOATS, showing improvements in convergence speed, accuracy, and robustness compared to traditional WOA and other metaheuristic algorithms. After extensive testing against a challenging set of benchmark functions and engineering optimization problems, we conclude that our proposed method is well suited for tackling high-dimensional optimization tasks and constrained optimization problems, providing substantial computational efficiency gains and improved overall solution quality.

The management of electronic health records in modern healthcare systems is crucial. To ensure confidentiality, integrity, and accessibility, regulations such as GDPR and HIPAA have been established in several countries. Various research studies have proposed the integration of blockchains into these systems to tackle some of these security issues. However, most healthcare infrastructures rely on legacy systems that lack interoperability, and thus the fusion of these with blockchain technology for managing medical records would be ineffective and costly. In our work, we propose a blockchain-based scheme for secure authorization, action recording, and integrity perseverance that can be easily integrated into typical healthcare organizations while also being scaled and maintained effectively.

Accurate and secure Identification Friend or Foe (IFF) remains a fundamental component of contemporary military operations, particularly in light of the increasing deployment of unmanned aerial vehicles (UAVs). Traditional IFF systems, however, are predominantly centralized, rendering them susceptible to cyberattacks and single points of failure. To mitigate these vulnerabilities, this study proposes a three-layer blockchain architecture that distributes IFF functionalities across Edge, Regional, and Central nodes. Within this framework, local detections and lightweight block production are executed at the Edge layer, while Regional nodes aggregate these blocks to sustain theater-wide situational awareness. Final consensus is achieved at the Central layer through the Practical Byzantine Fault Tolerance (PBFT) protocol. By decentralizing trust and auditing mechanisms, the proposed architecture enhances resilience against spoofing and denial-of-service attacks, supporting robust friend-or-foe classification even in adversarial environments. The system’s performance is evaluated within a simulation environment where UAV state transitions follow a Markov-based model, subject to stochastic variations, and network communications adhere to an empirical channel model that accounts for path loss, shadowing, and fading. The results demonstrate that block production, transaction throughput, and consensus success rates scale effectively with an increasing number of regions and Edge nodes, affirming the architecture’s efficacy in facilitating timely, reliable, and highly scalable IFF operations in modern combat scenarios.