Digital passports for Unmanned Aerial Vehicles (UAVs) are used to create a unified system for tracking and identifying UAVs, which ensures compliance and security. A digital passport holds details like the owner's information, drone model, and activity history, thereby enabling easy tracking and identification of UAVs. However, the absence of decentralized and secure digital passport management systems for UAVs makes it challenging to ensure tamper-proof records and transparent ownership verification across borders. This paper proposes a proof of concept for a decentralized blockchain and Non-Fungible Tokens (NFTs)-based digital passport to improve the transparency, traceability, trust, and security of UAV preoperational certifications. The proposed solution secures UAVs' preoperational stages such as design, manufacturing, and distribution, integrating best practices from the Federal Aviation Administration (FAA) and the European Union Aviation Safety Agency (EASA) for standardized compliance. The proposed NFT-based digital passport consolidates certification records into a single verifiable document, providing access to compliance history. Four smart contracts are developed to enforce role-based access control, and off-chain decentralized storage using the InterPlanetary File System (IPFS) is employed to manage large UAV records. Evaluation through implementation and testing demonstrates the solution's effectiveness in managing UAV certification workflows and enforcing regulatory compliance. Security analysis shows robustness against unauthorized modifications and common vulnerabilities, while cost analysis assesses deployment viability across multiple blockchain networks. A comparison of the proposed solution with existing UAV compliance and certification frameworks shows that it effectively fills the gap by addressing preoperational certification. The smart contract code is publicly available on GitHub.
Recent revolutionary advancements in the services as observed with the use cases of Industry 5.0, consumer electronics 2.0/smart devices 2.0, digital healthcare ecosystem, Internet-of-Things (IoT), advanced digital finance/currency, and Non-Terrestrial Network (NTN) expansion, to name a few, have resulted in a spectacular growth in the number of wireless-connected devices. Subsequently, this has drastically increased the demands for network capacity, channel capacity, reliability, privacy, and security provisions. Despite that, the 5 th Generation (5G) of wireless communication networks has introduced various innovative services such as Ultra-Reliable Low Latency Communication (URLLCs), Massive Machine Type Communication (mMTCs), and Enhanced Mobile Broadband (eMBB). These services only support isolated operations and the requisite reliable service delivery remains a challenge. The Beyond 5G (B5G)/6 th Generation (6G) wireless networks aim at simultaneously providing multiple integrated services through intelligent network operations with ultra-high speed and reliability supporting integrated NTN and terrestrial networks. However, the prospect of such an extensively connected decentralized 3D wireless network also foresees security concerns, underscoring the necessity for seamless and infrastructurefree (decentralized) security solutions. The conventional security mechanisms are considered inadequate to ensure the security provisions of such extensive, decentralized, and heterogeneous networks. Physical Layer Security (PLS) is a promising technique to extend seamless and infrastructure-less security solutions, ensuring the availability, confidentiality, and integrity of legitimate transmissions. This paper provides a comprehensive overview with tutorials and presents the state-of-the-art of PLS, focusing mainly on NTN wireless communications. Furthermore, current research challenges, open issues, and future research directions are also thoroughly discussed in an amalgamation of various emerging 6G technologies. Finally, we provide an overview of implementation challenges in NTN and potential solutions to support the standardization progression of NTN in upcoming releases of 3 rd Generation Partnership Project (3GPP).
The increasing deployment of Unmanned Aerial Vehicles (UAVs) for military, commercial, and logistics applications has raised significant concerns regarding flight path privacy. Conventional UAV communication systems often expose flight path data to third parties, making them vulnerable to tracking, surveillance, and location inference attacks. Existing encryption techniques provide security but fail to ensure complete privacy, as adversaries can still infer movement patterns through metadata analysis. To address these challenges, we propose a zk-SNARK (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge)-based privacy preserving flight path authentication and verification framework. Our approach ensures that a UAV can prove its authorisation, validate its flight path with a control centre, and comply with regulatory constraints without revealing any sensitive trajectory information. By leveraging zk-SNARKs, the UAV can generate cryptographic proofs that verify compliance with predefined flight policies while keeping the exact path and location undisclosed. This method mitigates risks associated with real-time tracking, identity exposure, and unauthorised interception, thereby enhancing UAV operational security in adversarial environments. Our proposed solution balances privacy, security, and computational efficiency, making it suitable for resource-constrained UAVs in both civilian and military applications.
Unmanned aerial vehicles (UAVs) are one of the most popular and effective systems in various industrial applications such as surveillance, security, and infrastructure inspection. It is gradually becoming an essential part of navigation as a consequence of high progress in military and civilian missions. Path planning of UAVs in military and civilian missions or in unknown and restricted environments is one of the biggest problems facing the operation of UAVs. This problem is not only searching for a path from an initial point to the final but also linked to find an optimal among all possible paths and provides collision avoidance. By examining the best path for UAVs, there is a need for the consideration of various other issues such as security and privacy, turning angle, overtake speed of obstacle, etc. The fundamental problem of UAVs is finding an optimal and secure route in a challenging environment. To overcome these challenges, many researchers have used optimization techniques such as ant colony, particle swarm, artificial bee colony, etc. with planning and coordination. In this paper, a blockchain-based solution is used to secure and authenticate UAVs. Hence, we propose a blockchain-based method that uses a genetic algorithm, which solves both constrained and unconstrained optimization problems. The purpose of this technique is to locate the best possible flight path for the UAVs in a three-dimensional setting. In a genetic algorithm, each iteration is designed to surpass the previous one in terms of improvement. To achieve an ideal route, solving the travelling salesman problem is a crucial step in the proposed approach. Consequently, the blockchain technology offers a reliable wireless communication and a dependable network for UAVs path planning, guaranteeing efficient service. Simulation results demonstrate the impact of the proposed scheme. They show that a genetic algorithm is suitable for optimal path planning for UAVs.
Unmanned Aerial Vehicles (UAVs) are pivotal in enhancing connectivity in diverse applications such as search and rescue, remote communications, and battlefield networking, especially in environments lacking ground-based infrastructure. This paper introduces a novel approach that harnesses Multi-Agent Deep Reinforcement Learning to optimize UAV communication systems. The methodology, centered on the Independent Proximal Policy Optimization technique, significantly improves fairness, throughput, and energy efficiency by enabling UAVs to autonomously adapt their operational strategies based on real-time environmental data and individual performance metrics. Moreover, the integration of Distributed Ledger Technologies with Multi-Agent Deep Reinforcement Learning enhances the security and scalability of UAV communications, ensuring robustness against disruptions and adversarial attacks. Extensive simulations demonstrate that this approach surpasses existing benchmarks in critical performance metrics, highlighting its potential implications for future UAV-assisted communication networks. By focusing on these technological advancements, the groundwork is laid for more efficient, fair, and resilient UAV systems.
This study introduces the Distributed Drone Reputation Management (DDRM) framework, designed to fortify trust and authenticity within the Internet of Drone Things (IoDT) ecosystem. As drones increasingly play a pivotal role across diverse sectors, integrating crowdsourced drone services within the IoDT has emerged as a vital avenue for democratizing access to these services. A critical challenge, however, lies in ensuring the authenticity and reliability of drone service reviews. Leveraging the Ethereum blockchain, DDRM addresses this challenge by instituting a verifiable and transparent review mechanism. The framework innovates with a dual-token system, comprising the Service Review Authorization Token (SRAT) for facilitating review authorization and the Drone Reputation Enhancement Token (DRET) for rewarding and recognizing drones demonstrating consistent reliability. Comprehensive analysis within this paper showcases DDRM's resilience against various reputation frauds and underscores its operational effectiveness, particularly in enhancing the efficiency and reliability of drone services.
With the continuous development of UAV technology, the application of UAV swarm in the military field is gradually becoming the focus of research around the world. Although it can bring a series of benefits in autonomous cooperation, the traditional UAV management technology is prone to hacker attacks due to many security issues such as a single point of failure brought by centralized management. Because of the advantages of distributed, tamper-proof, and traceability, blockchain is applied to UAV swarm to solve some of the security problems caused by centralized management. However, due to the limitations of its consensus algorithm Practical Byzantine Fault Tolerance (PBFT), its communication complexity will increase rapidly with the increase of the number of nodes, which also leads to the poor scalability of the algorithm and can only be applied to small-scale networks. To use the PBFT algorithm in large-scale networks such as UAV swarm, a dynamic and highly trusted PBFT (DTPBFT) algorithm is proposed in this paper. Firstly, a new consensus algorithm model including consensus layer and verification layer is designed. Then, a consensus node election scheme based on trust mechanism is proposed under this model. The trust degree of nodes in the blockchain network is comprehensively evaluated by selecting several representative indicators, and the weight factor of each indicator is calculated by entropy weight method. It not only reduces the communication complexity, but also ensures the reliability and dynamic update of consensus nodes. Experiments show that when the number of UAVs is 200, the consensus time of DTPBFT is 0.24 s, which indicates that this algorithm can support large-scale UAV swarm without causing communication congestion, so it has good scalability. In addition, experiments also show that DTPBFT can tolerate more than 13 malicious nodes, which improves the fault tolerance rate of PBFT.
Kyriaki A. Tychola, Konstantinos Voulgaridis, Θωμάς Λάγκας
The Internet of Drones (IoD) is a decentralized network linking drones’ access to controlled airspace, providing high adaptability to complex scenarios and services to various drone applications, such as package delivery, traffic surveillance, and rescue, including navigation services. Unmanned Aerial Vehicles (UAVs), combined with IoD principles, offer numerous strengths, e.g., high mobility, wireless coverage areas, and the ability to reach inaccessible locations, including significant improvements such as reliability, connectivity, throughput, and decreased delay. Additionally, emerging blockchain solutions integrated within the concept of the IoD enable effective outcomes that surpass traditional security approaches, while enabling decentralized features for smart human-centered applications. Nevertheless, the combination of the IoD and blockchain faces many challenges with emerging open issues that require further investigation. In this work, we thoroughly survey the technological concept of the IoD and fundamental aspects of blockchain, while investigating its contribution to current IoD practices, the impact of novel enabling technologies, and their active role in the combination of the corresponding synergy. Moreover, we promote the combination of the two technologies by researching their collaborative functionality through different use cases and application fields that implement decentralized IoD solutions and highlighting their indicative benefits, while discussing important challenges and future directions on open issues.
Recent advances in aerial robotics and wireless transceivers have generated an enormous interest in networks constituted by multiple compact unmanned aerial vehicles (UAVs). UAV adhoc networks, i.e., aerial networks with dynamic topology and no centralized control, are found suitable for a unique set of applications, yet their operation is vulnerable to cyberattacks. In many applications, such as IoT networks or emergency failover networks, UAVs augment and provide support to the sensor nodes or mobile nodes in the ground network in data acquisition and also improve the overall network performance. In this situation, ensuring the security of the adhoc UAV network and the integrity of data is paramount to accomplishing network mission objectives. In this paper, we propose a novel approach to secure UAV adhoc networks, referred to as the blockchain-assisted security framework (BCSF). We demonstrate that the proposed system provides security without sacrificing the performance of the network through blockchain technology adopted to the priority of the message to be communicated over the adhoc UAV network. Theoretical analysis for computing average latency is performed based on queuing theory models followed by an evaluation of the proposed BCSF approach through simulations that establish the superior performance of the proposed methodology in terms of transaction delay, data secrecy, data recovery, and energy efficiency.
Rawabi Aldossri, Ahmed Aljughaiman, Abdullah Albuali
This paper presents a systematic literature review investigating the integration of lightweight blockchain and fog computing technologies to enhance the security and operational efficiency of drones. With a focus on critical applications such as military surveillance and emergency response, this review examines how the combination of blockchain’s secure, decentralized ledger and fog computing’s low-latency, localized data processing can address the unique challenges of drone operations. By compiling and analyzing current research, this study highlights innovative approaches and solutions that leverage these technologies to improve data integrity, reduce communication latency, and facilitate real-time decision-making in drone missions. Our findings underscore the significant potential of this technological integration to advance the capabilities and reliability of drones in high-stakes scenarios.
Runchen Xu, Zheng Chang, Xinran Zhang, Timo Hämäläinen
Unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) systems have emerged as a promising technology with the capability to expand terrestrial networks. UAVs, working as edge computing nodes and mobile base stations, can be deployed closer to user equipment (UEs). However, with the rapid increase of UEs, the scarcity of spectrum resources and computing resources has become a critical challenge for future mobile communication systems. Additionally, the inherent characteristics of wireless transmission and untrusted broadcasting pose significant security and privacy concerns for multi-UAV networks. To address these issues, this paper presents a blockchain-based resource trading mechanism (BRTM) and a double auction-based resource trading algorithm (DARA) for multi-UAV edge computing systems. It combines blockchain technology with double auction theory to ensure the security and fairness of resource trading. The relations between UEs and UAVs as a two-stage Stackelberg game is formulated and a pricing-based incentive strategy is proposed. The proposed scheme encourages active participation from both UEs and UAVs while maximizing the sum of their utilities. The security assessment and numerical outcomes show that the proposed method is effective and outperforms other benchmark schemes.
Sana Hafeez, Runze Cheng, Lina Mohjazi, Yao Sun · 5 authors
Unmanned Aerial Vehicles (UAVs) have significant potential for agile communication and relief coordination in post-disaster scenarios, especially when conventional ground infrastructure is compromised. However, effectively coordinating and securing swarms of heterogeneous UAVs from multiple service providers presents critical challenges related to privacy, scalability, lightweight consensus protocols, and cybersecurity resilience. This study proposes a blockchain-enabled UAV coordination framework that leverages consensus mechanisms, smart contracts, and cryptographic techniques to address these challenges. First, a consortium blockchain architecture is introduced, integrating Zero-Knowledge Proofs (ZKPs) to enable privacy-preserving, multi-agency coordination while ensuring access control and data security. Second, a hybrid Delegated Proof-of-Stake–Practical Byzantine Fault Tolerance (DPoS-PBFT) consensus protocol is developed to optimise security, efficiency, and resilience against node failures in resource-constrained UAV networks. Third, a decentralized flocking algorithm is proposed to enable adaptive and autonomous UAV cluster operations under dynamically changing connectivity conditions, ensuring seamless disaster relief functions. Comprehensive simulations show that the proposed system scales efficiently to 500 UAV nodes while maintaining high throughput and low latency, with only a 50-ms increase in latency from 10 to 500 nodes. The framework demonstrates strong cyber resilience, remaining robust under denial-of-service (DoS), spoofing, and tampering attacks. Furthermore, communication latencies remain under 10 milliseconds, with median values of approximately 2–3 ms, achieved through self-optimizing network intelligence. The results validate the proposed system as a secure, scalable, and high-performance solution for UAV-enabled disaster response, ensuring reliable emergency communication and efficient resource allocation in critical environments.
Sana Hafeez, Mahmoud A. Shawky, Mohammad Al-Quraan, Lina Mohjazi · 6 authors
Unmanned aerial vehicles (UAV), an emerging architecture that embodies flying ad-hoc networks, face critical privacy and security challenges, mainly when engaged in data-sensitive missions. Therefore, message authentication is a crucial security feature in drone communications. This paper presents a Blockchain-based Efficient, and Trusted Authentication scheme for UAV communication, BETA-UAV, which exploits the inherent properties of blockchain technology concerning memorability and is immutable to record communication sessions via transactions using a smart contract. The smart contract in BETA-UAV allows participants to publish and call transactions from the blockchain network. Furthermore, transaction addresses are proof of freshness and trustworthiness for subsequent transmissions. Furthermore, we investigated their ability to resist active attacks, such as impersonation, replaying, and modification. In addition, we evaluate the gas costs associated with the functions of the smart contract by implementing a BETA-UAV on the Ethereum public blockchain. A comparison of the computation and communication overheads shows that the proposed approach can save significant costs over traditional techniques.
Sana Hafeez, Runze Cheng, Lina Mohjazi, Muhammad Ali Imran · 5 authors
Emergency communication is critical but challenging after natural disasters when the ground infrastructure is devastated. Unmanned aerial vehicles (UAVs) have enormous potential for agile relief coordination in such scenarios. However, effectively leveraging UAV fleets poses additional challenges, in terms of security, privacy, and efficient collaboration across response agencies. This paper presents a robust blockchain-enabled framework to address these challenges by integrating a consortium blockchain model, smart contracts, and crypto-graphic techniques to securely coordinate UAV fleets for dis-aster response. Specifically, we make two key contributions: a consortium blockchain architecture for secure and private multi-agency coordination and an optimized consensus protocol balancing efficiency and fault tolerance using a delegated proof of stake practical Byzantine fault tolerance (DPoS-PBFT). Com-prehensive simulations show the framework's ability to enhance transparency, automation, scalability, and cyber-attack resilience for UAV coordination in post-disaster networks.
The widespread use of UAVs in smart cities for tasks like traffic monitoring and environmental data collection creates significant privacy and security concerns due to the transmission of sensitive data. Traditional UAV-MEC systems with centralized data processing expose this data to risks like breaches and manipulation, potentially hindering the adoption of these valuable technologies. To address this critical challenge, we propose UBFL, a novel privacy-preserving federated learning mechanism that integrates blockchain technology for secure and efficient data sharing. Unlike traditional methods relying on differential privacy (DP), UBFL employs an adaptive nonlinear encryption function to safeguard the privacy of UAV model updates while maintaining data integrity and accuracy. This innovative approach enables rapid convergence, allowing the base station to efficiently identify and filter out severely compromised UAVs attempting to inject malicious data. Additionally, UBFL incorporates the Random Cut Forest (RCF) anomaly detection algorithm to actively identify and mitigate poisoning data attacks. Extensive comparative experiments on benchmark datasets CIFAR10 and Mnist demonstrably showcase UBFL's effectiveness. Compared to DP-based methods, UBFL achieves accuracy (99.98%), precision (99.93%), recall (99.92%), and F-Score (99.92%) in privacy preservation while maintaining superior accuracy. Notably, under data pollution scenarios with varying attack sample rates (10%, 20%, and 30%), UBFL exhibits exceptional resilience, highlighting its robust capabilities in securing UAV gradients within MEC environments.
Syed Faisal Abbas Shah, Tehseen Mazhar, Tamara Al Shloul, Tariq Shahzad · 7 authors
Real-time data gathering, analysis, and reaction are made possible by this information and communication technology system. Data storage is also made possible by it. This is a good move since it enhances the administration and operation services essential to any city's efficient operation. The idea behind "smart cities" is that information and communication technology (ICTs) need to be included in a city's routine activities in order to gather, analyze, and store enormous amounts of data in real-time. This is helpful since it makes managing and governing urban areas easier. The "drone" or "uncrewed aerial vehicle" (UAV), which can carry out activities that ordinarily call for a human driver, serves as an example of this. UAVs could be used to integrate geospatial data, manage traffic, keep an eye on objects, and help in an emergency as part of a smart urban fabric. This study looks at the benefits and drawbacks of deploying UAVs in the conception, development, and management of smart cities. This article describes the importance and advantages of deploying UAVs in designing, developing, and maintaining in smart cities. This article overviews UAV uses types, applications, and challenges. Furthermore, we presented blockchain approaches for addressing the given problems for UAVs in smart research topics and recommendations for improving the security and privacy of UAVs in smart cities. Furthermore, we presented Blockchain approaches for addressing the given problems for UAVs in smart cities. Researcher and graduate students are audience of our article.
Abstract The wide applications of the Internet of Drones (IoD), ranging from package delivery to surveillance, attract the attention of industrialists and academicians. Drones are given the task of obtaining sensitive field information within the flying zone in real‐time. Hence, it is important to tackle the privacy and security issues associated with drones that are employed in these kinds of situations. Also, when the drones move to the new unmanned aerial vehicle (UAV) operator coverage area, the drones are required to execute the authentication process again, which affects the performance of IoD. To overcome the above‐said shortcomings, a physically secure and privacy‐preserving blockchain enabled authentication method is proposed in this paper. The blockchain network permits drones to perform quick re‐authentication by transferring drone authentication codes to the following UAV operators. In the proposed work, the drone does not need to store the secret keys to perform anonymous authentication, and it provides physical security for the drones. When compared to competing techniques, the proposed scheme delivers the needed security features while incurring lower storage, computational, and communication costs.
Flying Ad Hoc Networks (FANET) is an emerging area of research due to its low cost, high coverage and fast transmission features. In these networks, the flying nodes are connected with ground stations and communicate wirelessly, especially when the networks are congested and complex. Due to mobility, and lack of predefined infrastructure, these networks have suffered from various security and trust issues. The traditional trust and security solutions are designed for ground networks and are not feasible for these networks. This paper proposes a trust and authentication model including Trust Establishment Mechanism for FANET (TEM-FANET) and authentication system by using Block-chain method. The trust is calculated to evaluate the node’s trust status and ensure the existence of the trustworthy nodes by using direct, indirect, and cumulative trust values. Whereas the authentication system is utilizing blockchain technology for nodes authentication and evaluate its feasibility. The proposed model is lightweight and able to monitor the node’s behavior and compute the trusted quality and broadcast the node status with neighbor nodes. The proposed model is also integrated with ground stations for record keeping and decision-making processes. The proposed model is evaluated in simulation with state-of-the-art trust solutions where the results show the better performance in terms of overhead, data delivery, node detection rate, and computational time.
Unmanned aerial vehicles (UAVs) have emerged as pivotal roles within internet of vehicles (IoV), serving as mobile base stations. However, while expanding coverage and improving mobility, the deployment of UAVs also poses a threat to the integrity and privacy of sensitive data due to open wireless communication channels in IoV. Therefore, preventing unauthorized access and data tampering is critically important between UAVs and vehicles. For the authenticity and legitimacy of the UAV certificate, existing authentication approaches may lead to significant challenges in key management overhead or dependence on a trusted third party. In this paper, a blockchain-based authentication scheme for UAV-assisted IoV system (BASUV) is proposed. This solution enables dependable UAV registration and authentication services, and permits the dynamic addition and removal. Specifically, blockchain is introduced to achieve the decentralized management and distributed trust of the UAV certificate ledger. Furthermore, to prevent information tampering and identity deception, we design CMPES, a novel combined scheme based on multiple public key generators (PKGs) for encryption and signature. Identical key pair in encryption and signature can reduce key generation and management overhead. The security and experimental analysis demonstrates the effectiveness and efficiency of the proposed scheme.
Hengchang Pan, Y. W. Wang, Wei Wang, Ping Cao · 6 authors
Efficient and trusted regulation of unmanned aerial vehicles (UAVs) is an essential but challenging issue in the future era of the Internet of Low-altitude Intelligence, due to the difficulties in UAVs’ identity recognition and location matching, potential for falsified information reporting, etc. To address this challenging issue, in this paper, we propose a blockchain-based UAV location authentication scheme, which employs a distance bounding protocol to establish a location proof, ensuring the authenticity of UAV positions. To preserve the privacy of UAVs, anonymous certificates and zero-knowledge proof are used. The security of the proposed scheme is analyzed. Experiments demonstrate the efficiency and feasibility of the proposed scheme.
Due to its diverse and promising use cases, including civilian, military, and commercial, the Internet of Drones (IoD) has quickly become a hot issue in academic and industry circles. Concerns about drone privacy and security are also growing at the same rate. Drones from different flying zones frequently work together in the IoD to accomplish the same mission, necessitating the development of trust among untrusted domains. Recently, some researchers have used blockchain in their authentication scheme to establish trust across different domains. However, the integration led to significant communication, computation and storage overheads and the loss of crucial security features like anonymity or unlinkability. To address these concerns, we develop a cost-effective key exchange protocol for cross-domain IoD communications through the judicious use of the blockchain. Specifically, we employ Chebyshev's chaotic map as the crypto-system, and the ledger keeps only the public keys of the drones, resulting in a significant decrease in storage and computation overheads. The proposed protocol not only complies with the stringent Canetti and Krawczyk adversary model but also satisfies the essential security requirements for IoD, such as anonymity and unlinkability. Using informal justification, formal proof, and automated security reasoning in addition to a comparative performance evaluation, this research substantiates its claims.
Chengzu Dong, Shantanu Pal, Qi An, Aiting Yao · 11 authors
This paper presents a novel architecture that utilizes the Zero Trust Principle to facilitate blockchain-enabled Unmanned Aerial Vehicle (UAV) delivery systems, emphasizing recipient privacy, verification, and continuous authentication. By integrating blockchain’s decentralization and transparency with a Zero Trust model, the architecture ensures robust security and access control. The blockchain-based architecture guarantees data integrity and resilience, while advanced cryptographic techniques, including homomorphic encryption, ensure long-term security. Ongoing security assessment and improvement are facilitated through the maturity model’s integration with blockchain technology. This innovative approach effectively mitigates cyber risks, safeguards recipient data privacy, it initiative promotes the secure and efficient use of UAVs in logistics. It emphasizes the importance of maintaining strict access controls and trust boundaries. Through adaptable security evaluations, the model addresses evolving threats, ensuring a secure environment for UAV integration into the modern supply chain while prioritizing recipient privacy and security.
This paper develops a cutting-edge multimodal federated learning framework, integrated with distributed ledger technologies, designed specifically for UAV delivery scenarios. The framework adopts various data modalities, including user pictures, behavior, and location, to dynamically optimize delivery routes and schedules, thus enhancing both user privacy and security of the delivery process. By employing federated learning, this framework allows data to be processed locally on individual devices, significantly enhancing both user privacy and data integrity. The integration of distributed ledger technology ensures that all updates to the federated model are not only immutable and traceable, but also secure. Through comprehensive evaluations, our framework shows outstanding improvements in both the efficiency and security of UAV deliveries. These findings show the transformative potential of our approach to establish user-centric, efficient, and secured UAV delivery systems.
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.