Blockchain Papers

Xihan Zhang, Jiashuo Zhang, Jianbo Gao, Libin Xia · 7 authors

No abstract is available for this record.

Hayla Nahom Abishu, Guolin Sun, Yasin Habtamu Yacob, Gordon Owusu Boateng · 6 authors

Sixth generation (6G) networks deploy unmanned aerial vehicles and mobile edge computing to provide collaborative computing and reliable connectivity for resource-limited mobile devices (MDs). However, due to the untrusted and broadcast nature of wireless transmission among communicating MDs and computing resource providers, ensuring the security of resource transactions will be challenging. Blockchain-based resource-sharing systems have been proposed to address security issues. However, these systems use existing consensus mechanisms like Proof-of-Work that consume massive amounts of system resources. In addressing this, some studies attempted to use single-agent deep reinforcement learning (DRL) in leader selection. Nevertheless, these solutions overlooked the intelligence and flexibility of blockchain configuration, and a single-point of failure can cause the system to fail. We propose a multiagent distributed deep deterministic policy gradient (MAD3PG)-assisted consensus mechanism for blockchain-based collaborative resource sharing to address these issues. First, we propose a stochastic game-based incentive-mechanism to encourage consensus nodes to participate in transaction validation. Then, we formulate the optimization problem of node selection and blockchain configuration as a Markov decision process and solve it with the MAD3PG algorithm. With MAD3PG, the agents select consensus nodes based on their experience and available resources and dynamically adjust blockchain settings. The simulation results show that MAD3PG outperforms the benchmarks in maximizing throughput and incentive while minimizing block production latency.

Keke Huang, Huidan Hu, Changlu Lin

Unmanned aerial vehicles (UAVs, also known as Drones) have been widely employed in military defense and civilian service. However, as UAVs communicate over insecure open wireless channels, the security challenges and privacy concerns are becoming increasingly prominent. Moreover, some existing schemes to achieve authentication and key agreement (AKA) among UAVs are spliced with the assistance of two UAV-2-GCS mechanisms, which are not flexible enough to be applied in the Internet of Drones (IoD) scenarios. This article proposes a blockchain-assisted AKA scheme for UAVs networks (BAKAS-UAV) referred to as BAKAS-UAV, which addresses security and privacy concerns and overcomes high computational and communication costs in the IoD. A blockchain-based network model is presented in which the ground station acts as an edge node and manages the blockchain, which assists AKA. Based on the network model, both types of AKA mechanisms, UAV-2-GCS and UAV-2-UAV, are proposed, respectively. In particular, the ground control station (GCS) does not participate in the AKA of UAV-2-UAV process; only upon the process is completed the two UAVs synchronize the updated information with GCS. We also implement a smart contract as the authentication service, and the experimental implementation demonstrates the availability of our scheme in IoD. Physical unclonable functions (PUFs) is introduced on the UAVs side to defend against physical capture attacks and also to implement AKA mechanisms. The semantic security is proved formally based on the real-or-random (ROR) model, and the informal analysis shows that the scheme satisfies the demanded security requirements. The scheme’s performance is evaluated by simulating the UAVs and GCS settings with Raspberry Pi 4B and MacOS platforms, respectively, with implementation of several cryptographic primitives. The experimental results show that BAKAS-UAV achieves high efficiency.

Farman Ali, Muhammad Ahtasham, Zahra Anfaal

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.

Junaid Akram, Ali Anaissi

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.

Runqun Xiong, Qing Xiao, Z. Wang, Zhuqing Xu · 5 authors

No abstract is available for this record.

Die Wang, Yunjian Jia, Liang Liang, Kaoru Ota · 5 authors

Recently, unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) has emerged as a practical paradigm to enable low latency computing offloading for dispersed users in the fifth generation (5G) wireless networks. However, severe security and privacy concerns are associated with the open environment between the UAVs and edge computing nodes. In this paper, we address these challenges by integrating blockchain technology into UAV-enabled MEC networks. We present an innovative Delegated Proof of Stake (DPoS) consensus mechanism where the UAV is a primary node and verification nodes are edge computing nodes selected by the reputation mechanism. To enhance mobile users’ Quality of Service (QoS), edge computing resources need to be allocated among UAV and verification nodes. Based on this, we propose the trading mechanism for resource pricing and allocation based on the two-stage Stackelberg differential game. Meanwhile, dynamic states of user demands and verification node reputations are modeled using differential equations as constraints of the objective function at various stages to simulate adaptive service requests for users and incentivize active participation for verification nodes. Simulation results prove the effectiveness of the proposed resource trading scheme and demonstrate the equilibrium and convergence status of resource pricing and allocation for edge computing.

Pengbin Han, Xinfeng Wu, Aina Sui

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.

Ushasri Peddibhotla, Randhir Kumar, C C Sobin, Prabhat Kumar · 6 authors

The integration of Unmanned Aerial Vehicles (UAVs) in smart agriculture has significantly enhanced precision farming practices, enabling real-time monitoring and data collection for improved crop management. However, the reliance on wireless communication in UAV networks poses security challenges that can compromise the integrity and confidentiality of sensitive agricultural data. This paper proposes a novel approach to address these concerns through the incorporation of blockchain technology for secure communication in UAV networks deployed for smart agriculture. The proposed system leverages the decentralized and tamper-resistant nature of blockchain to establish a trust-based communication framework. Each UAV node in the network is equipped with a blockchain-enabled communication protocol, ensuring that data exchanges are securely recorded in an immutable ledger. This not only enhances data integrity but also mitigates the risk of unauthorized access and manipulation. To facilitate secure communication, smart contracts are employed to automate and enforce predefined rules governing data transactions within the UAV network. This ensures that only authenticated and authorized entities can access and modify agricultural data, fostering a transparent and accountable ecosystem. Additionally, cryptographic techniques such as public-key encryption enhance the confidentiality of transmitted data, safeguarding sensitive information from eavesdropping and unauthorized interception. The proposed blockchain-enabled secure communication system is further enhanced by incorporating consensus mechanisms that validate and confirm the integrity of data across the network. By doing so, the trustworthiness of the entire UAV network is strengthened, reducing the likelihood of malicious activities and enhancing overall system resilience.

Chen Wang, Daosen Zhai, Ruonan Zhang, Huan Li · 5 authors

Integrating the unmanned aerial vehicles (UAVs) assisted mobile edge computing (MEC) network with the blockchain technology emerges its superiority in the network utilization, differentiated service, and security, which has been regarded as a promising technique for time-critical applications. In this paper, we propose a UAV-assisted MEC network architecture and a comprehensive data processing flow, where the UAVs cooperate with the base station in computation as edge servers and act as blockchain nodes. We formulate an optimization problem that jointly considers UAVs’ position, data offloading, and resource allocation for minimizing the total time consumption of data processing. To address this problem, we decouple it as three tractable subproblems and propose a Block Coordinate Descent (BCD)-based iterative algorithm. In addition, we analyze the task migration and resource allocation problem in computation, and obtain analytical solutions by the Karush-Kuhn-Tucker (KKT) conditions. The simulated results indicate that the proposed algorithm leads to substantial performance gains.

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.

Mohammed A. Alqarni

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.

Yi Zhang, Peiying Zhang, Mohsen Guizani, Jianyong Zhang · 8 authors

No abstract is available for this record.

Özlem Sabuncu, Bülent Bilgehan

No abstract is available for this record.

Tanya Garg, Shashank Gupta, Mohammad S. Obaidat, Meghna Raj

No abstract is available for this record.

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.

Maha Kadadha, Rabeb Mizouni, Shakti Singh, Hadi Otrok · 5 authors

No abstract is available for this record.

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.

Liang Xie, Zhou Su, Nan Chen, Yiliang Liu · 5 authors

Empowered by crowdsensing technology, unmanned aerial vehicles (UAVs) equipped with rich sensors can perform sensing tasks in extreme scenarios. However, due to the selfishness and distrust of UAVs, some malicious UAVs with insufficient resources may provide false sensing data to the task publishers. In addition, the centralized sensing platform is vulnerable to various attacks (e.g., data tampering attack and single point of failure) in traditional crowdsensing, resulting in degraded data quality and severe security issues. To cope with these problems, we propose a blockchain-based crowdsensing framework with reputation incentive (BCFR) for UAV-assisted mobile crowdsensing. Specifically, a reputation-based incentive scheme is first proposed to relate the behavior of each UAV with its reputation, and then to choose UAVs with high reputation to perform sensing tasks, thereby improving the security of sensing data sharing. Afterwards, we design a blockchain-based secure data transmission scheme to securely record data transactions of UAVs. Furthermore, UAVs may be reluctant to perform compute-intensive mining tasks due to their limited computing capabilities. Therefore, a two-stage Stackelberg game is introduced to motivate UAVs to participate in the block creation process. In a more realistic scenario, where participants are bounded rational, prospect theory (PT) is utilized to capture the potential subject perceptions of UAVs. Finally, simulation results and security analysis demonstrate that the proposed BCFR scheme can effectively improve the probability of successful mining and ensure the security of data sharing.

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.

Chaoyang Zhu, Zhu Xiao, Tuanfa Qin

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.

Zhihao Li, Zhihao Li, Qi Chen, Jin Li · 8 authors

No abstract is available for this record.