Maninderpal Singh, Gagangeet Singh Aujla, Rasmeet Singh Bali
Abstract Internet of Drones (IoD) facilitates the autonomous operations of drones into every application (warfare, surveillance, photography, etc) across the world. The transmission of data (to and fro) related to these applications occur between the drones and the other infrastructure over wireless channels that must abide to the stringent latency restrictions. However, relaying this data to the core cloud infrastructure may lead to a higher round trip delay. Thus, we utilize the cloud close to the ground, i.e., edge computing to realize an edge-envisioned IoD ecosystem. However, as this data is relayed over an open communication channel, it is often prone to different types of attacks due to it wider attack surface. Thus, we need to find a robust solution that can maintain the confidentiality, integrity, and authenticity of the data while providing desired services. Blockchain technology is capable to handle these challenges owing to the distributed ledger that store the data immutably. However, the conventional block architecture pose several challenges because of limited computational capabilities of drones. As the size of blockchain increases, the data flow also increases and so does the associated challenges. Hence, to overcome these challenges, in this work, we have proposed a derived blockchain architecture that decouples the data part (or block ledger) from the block header and shifts it to off-chain storage. In our approach, the registration of a new drone is performed to enable legitimate access control thus ensuring identity management and traceability. Further, the interactions happen in the form of transactions of the blockchain. We propose a lightweight consensus mechanism based on the stochastic selection followed by a transaction signing process to ensure that each drone is in control of its block. The proposed scheme also handles the expanding storage requirements with the help of data compression using a shrinking block mechanism. Lastly, the problem of additional delay anticipated due to drone mobility is handled using a multi-level caching mechanism. The proposed work has been validated in a simulated Gazebo environment and the results are promising in terms of different metrics. We have also provided numerical validations in context of complexity, communication overheads and computation costs.
In recent years, with the continuous development of internet of things (IoT) technology, many fields have benefited a lot, including the maritime transportation system (MTS). But there are also corresponding risks, such as security and privacy, interference attacks, ransomware attacks, and so on. How to ensure the reliability and efficiency of information transmission is very important for maritime transportation system. In order to solve this problem, we propose an IoT-enabled maritime transport communication system, which is a distributed system composed of base stations and offshore buoys, and uses the unique structure of the blockchain to solve the problems of security and reliability in the network. There are two main advantages: First, the decentralized network is reliable and can handle node failures. Second, the use of blockchain technology can integrate computing resources into the entire network to support different tasks, while taking into account information security and transaction security. On this basis, with the help of edge computing technology, we have also improved the energy efficiency and performance of IoT devices in the system.
Ibrahim Abunadi, Maha M. Althobaiti, Fahd N. Al‐Wesabi, Anwer Mustafa Hilal · 8 authors
The evolving “Industry 4.0” domain encompasses a collection of future industrial developments with cyber-physical systems (CPS), Internet of things (IoT), big data, cloud computing, etc. Besides, the industrial Internet of things (IIoT) directs data from systems for monitoring and controlling the physical world to the data processing system. A major novelty of the IIoT is the unmanned aerial vehicles (UAVs), which are treated as an efficient remote sensing technique to gather data from large regions. UAVs are commonly employed in the industrial sector to solve several issues and help decision making. But the strict regulations leading to data privacy possibly hinder data sharing across autonomous UAVs. Federated learning (FL) becomes a recent advancement of machine learning (ML) which aims to protect user data. In this aspect, this study designs federated learning with blockchain assisted image classification model for clustered UAV networks (FLBIC-CUAV) on IIoT environment. The proposed FLBIC-CUAV technique involves three major processes namely clustering, blockchain enabled secure communication and FL based image classification. For UAV cluster construction process, beetle swarm optimization (BSO) algorithm with three input parameters is designed to cluster the UAVs for effective communication. In addition, blockchain enabled secure data transmission process take place to transmit the data from UAVs to cloud servers. Finally, the cloud server uses an FL with Residual Network model to carry out the image classification process. A wide range of simulation analyses takes place for ensuring the betterment of the FLBIC-CUAV approach. The experimental outcomes portrayed the betterment of the FLBIC-CUAV approach over the recent state of art methods.
Unmanned aerial vehicles (UAVs) extend the traditional ground-based Internet of Things (IoT) into the air. UAV mobile edge computing (MEC) architectures have been proposed by integrating UAVs into MEC networks during the current novel coronavirus disease (COVID-19) era. UAV mobile edge computing (MEC) shares personal data with external parties (such as edge servers) during intelligent medical analytics. However, this technique raises privacy concerns about patients’ health data. More recently, the concept of federal learning (FL) has been set up to protect mobile user data privacy. Compared to traditional machine learning, federated learning requires a decentralized distribution system to enhance trust for UAVs. Blockchain technology provides a secure and reliable solution for FL settings between multiple untrusted parties with anonymous, immutable, and distributed features. Therefore, blockchain-enabled FL provides both theories and techniques to improve the performance of intelligent UAV edge computing networks from various perspectives. This survey begins by discussing the current state of research on blockchain and FL. Then, compare the leading technologies and limitations. Second, we will discuss how to integrate blockchain and FL into UAV edge computing networks and the associated challenges and solutions. Finally, we discuss the fundamental research challenges and future directions.
The breakthrough of blockchain technology has facilitated the emergence and deployment of a wide range of unmanned aerial vehicles (UAV) networks-based applications. Yet, the full utilization of these applications is still limited due to the fact that each application is operating on an isolated blockchain. Thus, it is inevitable to orchestrate these blockchain fragments by introducing a cross-blockchain platform that governs the inter-communication and transfer of assets in the UAV networks context. In this paper, we survey the literature on the state-of-the-art cross blockchain frameworks to highlight the latest advances in the field. We also provide an up-to-date review of blockchain-based UAV networks applications. Based on the outcomes of our survey, we introduce a spectrum of scenarios related to UAV networks that may leverage the potentials of the currently available cross-blockchain solutions. Finally, we identify open issues and potential challenges associated with the application of a cross-blockchain scheme for UAV networks that will hopefully guide future research directions.
Recently, unmanned aerial vehicles (UAVs) have gained attention due to increased use-cases in healthcare, monitoring, surveillance, and logistics operations. UAVs mainly communicate with mobile base stations, ground stations (GS), or networked peer UAVs, known as UAV swarms. UAVs communicate with GS, or UAV swarms, over wireless channels to support mission-critical operations. Communication latency, bandwidth, and precision are of prime importance in such operations. With the rise of data-driven applications, fifth-generation (5G) networks would face bottlenecks to communicate at near-real-time, at low latency and improved coverage. Thus, researchers have shifted towards network designs that incorporate beyond 5G (B5G) networks for UAV designs. However, UAVs are resource-constrained, with limited power and battery, and thus centralized cloud-centric models are not suitable. Moreover, as exchanged data is through open channels, privacy and security issues exist. Federated learning (FL) allows data to be trained on local nodes, preserving privacy and improving network communication. However, sharing of local updates is required through a trusted consensus mechanism. Thus, blockchain (BC)-based FL schemes for UAVs allow trusted exchange of FL updates among UAV swarms and GS. To date, limited research has been carried out on the integration of BC and FL in UAV management. The proposed survey addresses the gap and presents a solution taxonomy of BC-based FL in UAVs for B5G networks due to the open problem. This paper presents a reference architecture and compares its potential benefits over traditional BC-based UAV networks. Open issues and challenges are discussed, with possible future directions. Finally, a logistics case study of BC-based FL-oriented UAVs in 6G networks is presented. The survey aims to aid researchers in developing potential UAV solutions with the key integrating principles over a diverse set of application verticals.
This research contributes to the security design of an advanced smart drone swarm network based on a variant of the Blockchain Governance Game (BGG), which is the theoretical game model to predict the moments of security actions before attacks, and the Strategic Alliance for Blockchain Governance Game (SABGG), which is one of the BGG variants which has been adapted to construct the best strategies to take preliminary actions based on strategic alliance for protecting smart drones in a blockchain-based swarm network. Smart drones are artificial intelligence (AI)-enabled drones which are capable of being operated autonomously without having any command center. Analytically tractable solutions from the SABGG allow us to estimate the moments of taking preliminary actions by delivering the optimal accountability of drones for preventing attacks. This advanced secured swarm network within AI-enabled drones is designed by adapting the SABGG model. This research helps users to develop a new network-architecture-level security of a smart drone swarm which is based on a decentralized network.
Haijun Liao, Zhao Wang, Zhenyu Zhou, Yang Wang · 7 authors
Power systems impose stringent security and delay requirements on computation offloading, which cannot be satisfied by existing power Internet of Things (PIoT) networks. In this paper, we tackle this challenge by combining blockchain, space-air-ground integrated PIoT (SAG-PIoT) and machine learning. Low earth orbit (LEO) satellites assist in broadcasting a consensus message to reduce the block creation delay, and unmanned aerial vehicles (UAVs) provide flexible coverage enhancement. Specifically, we propose a Blockchain and semi-distributed leaRning-based secure and low-latency electromAgnetic interferenCe-awarE computation offloading algorithm (BRACE) to minimize the total queuing delay under the long-term security constraint. First, the task offloading is decoupled from the computational resource allocation by Lyapunov optimization. Second, the task offloading problem is solved by the proposed federated deep actor-critic-based electromagnetic interference-aware task offloading algorithm (FDAC-EMI). Finally, the resource allocation problem is solved by smooth approximation and Lagrange optimization. Simulation results verify that BRACE achieves superior delay and security performance.
Abstract Alongside the rise of ‘last-mile’ delivery in contemporary urban logistics, drones have demonstrate commercial potential, given their outstanding triple-bottom-line performance. However, as a lithium-ion battery-powered device, drones’ social and environmental merits can be overturned by battery recycling and disposal. To maintain economic performance, yet minimise environmental negatives, fleet sharing is widely applied in the transportation field, with the aim of creating synergies within industry and increasing overall fleet use. However, if a sharing platform’s transparency is doubted, the sharing ability of the platform will be discounted. Known for its transparent and secure merits, blockchain technology provides new opportunities to improve existing sharing solutions. In particular, the decentralised structure and data encryption algorithm offered by blockchain allow every participant equal access to shared resources without undermining security issues. Therefore, this study explores the implementation of a blockchain-enabled fleet sharing solution to optimise drone operations, with consideration of battery wear and disposal effects. Unlike classical vehicle routing with fleet sharing problems, this research is more challenging, with multiple objectives (i.e., shortest path and fewest charging times), and considers different levels of sharing abilities. In this study, we propose a mixed-integer programming model to formulate the intended problem and solve the problem with a tailored branch-and-price algorithm. Through extensive experiments, the computational performance of our proposed solution is first articulated, and then the effectiveness of using blockchain to improve overall optimisation is reflected, and a series of critical influential factors with managerial significance are demonstrated.
The popularity of drones has increased their deployment in a wide range of applications like commercial delivery, industrial systems, monitoring, surveillance, and surveys. The facility of fast deployment and cost effectiveness make drones a potential choice for an aerial base station to serve user equipments (UEs) in a defined area. Drones are equipped with night vision cameras, advanced sensors, and GPS receivers, which make them able to capture data and either analyze it to discover new patterns or transmit it to the remote cloud for storage and processing. Furthermore, the drones data relaying system helps to extend the service coverage area to provide reliable communication connection to isolated UEs. However, the deployment of drones at remote locations relies only on GPS, and these systems are prone to various attacks that can lead to signal blockage. Data integrity and privacy are important issues that must be addressed before the deployment of drones in commercial sectors. Therefore, in this article, we propose a blockchain-based security approach for drone-to-everything communications wherein the location of drones is tracked based on the segment division of area under deployment. Moreover, we design a miner node selection algorithm that uses computational resources, battery status, and time of flight of a drone as parameters to select the miner node. The security evaluation of the proposed framework clearly shows the viability of blockchain in drone deployments across remote sites.
Unmanned Aerial Vehicle (UAV) communications have recently entered a new period of interest, motivated by technological advances and the gradual emergence of the Space-Air-Ground Integrated Network (SAGIN). The current survey aims to capture the use of UAVs in the SAGIN while highlighting the most promising open research topics. The traditional UAV network architecture is not adequate to meet the challenges presented by the SAGIN, and an effective and secure space-air-ground integrated UAV network needs to be constructed. Given its well-distributed management and consensus mechanism, blockchain technology can make up for the deficiency of the traditional UAV network. In this work, we review the role of UAVs in the SAGIN. Then, three applications of the blockchain-envisioned UAV network are introduced through several classifications. Future challenges and the corresponding open research topics are also described.
Over the years, the healthcare industry has transformed from being hospital-centric to patient-centric. This shift is mainly due to the convergence of emergent technologies such as Internet of Things (IoT)-based healthcare, fifth generation (5G)-assisted networking, and data-driven analytics through artificial intelligence. The convergence, referred to as Healthcare 5.0, has improved healthcare services to support real-time analytics, user mobility, remote monitoring, and personalized user experience through decentralized applications. However, the medical supply chain systems and delivery operations among healthcare stakeholders suffer from limitations of harsh environmental conditions due to restricted zones, rough terrains, war-prone areas, poor road conditions, congested traffic, and remote locations. Thus, the Internet of Drones (IoD) is deployed in Healthcare 5.0 supply chains to streamline and expedite the medical delivery process through open channels (i.e. the Internet). However, the Internet is an open channel that is prone to malicious activities which can violate the privacy and confidentiality of patient data. Blockchain is a promising technology that can handle the security and reliability of drone delivery among untrusted open channels. Motivated by the aforementioned facts, we propose GaRuDa, a blockchain-based drone delivery scheme for Healthcare 5.0 applications. The proposed scheme integrates IoD and blockchain through 5G-enabled tactile Internet to facilitate low-latency responsive delivery of medical supplies that can be chronologically monitored and tracked among different stakeholders. We compared the proposed scheme with the traditional medical delivery scheme with payment gateways to demonstrate its effectiveness in terms of data storage, computation, and communication costs. The simulation results obtained show that the average transaction cost has been reduced by ≈ 44.56 percent, and 5G tactile Internet has a reduced latency of 0.051 ms compared to 18.3 ms in 4G LTE service. The average communication overheads have reduced by ≈ 67.34 percent compared to traditional 4G LTE and orthogonal frequency-division multiplexing channels, which indicates the scheme's viability.
Abbas Yazdinejad, Elnaz Rabieinejad, Ali Dehghantanha, Reza M. Parizi · 5 authors
With the advancement of information and communication technology, Unmanned Aerial Vehicles (UAV), popularly known as drones, have also increased. The drones have been noted for their wide range of applications such as military, search and rescue operation, disaster detection and monitoring, agriculture, and delivery. Each type of drone has different characteristics and functionality based on its application, making them a security threat for some city zone. Therefore, there is an essential need for efficient drone management based on their type and application in different zones. To do this, we proposed a Machine learning (ML) based Software Defined Network (SDN) drone management framework. In this framework, the SDN controller uses ML with the drone’s radio frequency feature to detect its type and application and, according to its application, authenticate it and assign communication rules. SDN controller records authentication information in a DAG-based Distributed Ledger Technology (DLT) available for other SDN controllers. When a drone desires to migrate to another zone, the destination SDN controller can achieve authentication information by referring to DAG-based DLT, and there is no need for re-authentication. The experimental result shows authentication delay reduction in our proposed framework. Moreover, we adopted ML algorithms includes Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR), to evaluate our proposed framework in drone’s type classification. The result shows that the RF algorithm shows the best performance with 92.81% accuracy in the classification of the drone’s type.
Internet of Things (IoT) can be conveniently de-ployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. In this paper, we propose to employ unmanned aerial vehicles (UAVs) to assist the IoT data collection with blockchain-based security provisioning, towards efficient and safeguarded IoT operations. In particular, a blockchain with proof-of-stake (PoS) consensus mechanism is constructed among the UAVs with the collected IoT data. Correspondingly, we optimize the IoT communication and the UAV deployment for the maximum blockchain throughput considering the PoS procedure. The problem is solved with a deep deterministic policy gradient-based approach, where the power allocation is obtained with closed-form solutions and the UAV deployment is learned with actor-critic networks. Simulation results are provided to show the deployment and performance, corroborating the effectiveness of our proposal.
Basudeb Bera, Mohammad Wazid, Ashok Kumar Das, Joel J. P. C. Rodrigues
Drones, sometimes called unmanned aerial vehicles (UAVs), can be deployed in a flying Internet of Things (IoT)/Internet of Drones (IoD) environment to execute some specific tasks, like environmental monitoring, disaster management, aerial photography, monitoring and tracking of enemies at borders, and many more. For security reasons, the deployed drones can sense and collect the data from their surroundings, and then securely send the information to the ground station server. The ground station server then provides the collected data to the peer-to-peer cloud server (P2PCS) network after converting them into encrypted transactions in a secure way. Finally, the blocks are created from the encrypted transactions and added into a blockchain by applying consensus algorithms implemented by the P2PCS network. The deployed artificial intelligence (AI)-based big data analytics is required to predict the useful results from the collected and processed data. In this article, we propose a novel AI-envisioned smart-contract-based blockchain-enabled security framework for secure communication in IoD. The provided security analysis proves the security of the proposed framework against different potential attacks. The blockchain implementation of the proposed framework is then executed to identify its impact on the performance of the system.
Abdullah Ayub Khan, Zaffar Ahmed Shaikh, Asif Ali Laghari, Sami Bourouis · 6 authors
In this paper, we propose a secure blockchain-aware framework for distributed data management and monitoring. Indeed, images-based data are captured through drones and transmitted to the fog nodes. The main objective here is to enable process and schedule, to investigate individual captured entity (records) and to analyze changes in the blockchain storage with a secure hash-encrypted (SH-256) consortium peer-to-peer (P2P) network. The proposed blockchain mechanism is also investigated for analyzing the fog-cloud-based stored information, which is referred to as smart contracts. These contracts are designed and deployed to automate the overall distributed monitoring system. They include the registration of UAVs (drones), the day-to-day dynamic captured drone-based images, and the update transactions in the immutable storage for future investigations. The simulation results show the merit of our framework. Indeed, through extensive experiments, the developed system provides good performances regarding monitoring and management tasks.
Unmanned aerial vehicles (UAVs) are gaining immense attention due to their potential to revolutionize various businesses and industries. However, the adoption of UAV-assisted applications will strongly rely on the provision of reliable systems that allow managing UAV operations at high levels of safety and security. Recently, the concept of UAV traffic management (UTM) has been introduced to support safe, efficient, and fair access to low-altitude airspace for commercial UAVs. A UTM system identifies multiple cooperating parties with different roles and levels of authority to provide real-time services to airspace users. However, current UTM systems are centralized and lack a clear definition of protocols that govern a secure interaction between authorities, service providers, and end-users. The lack of such protocols renders the UTM system unscalable and prone to various cyber attacks. Another limitation of the currently proposed UTM architecture is the absence of an efficient mechanism to enforce airspace rules and regulations. To address this issue, we propose a decentralized UTM protocol that controls access to airspace while ensuring high levels of integrity, availability, and confidentiality of airspace operations. To achieve this, we exploit key features of the blockchain and smart contract technologies. In addition, we employ a mobile crowdsensing (MCS) mechanism to seamlessly enforce airspace rules and regulations that govern the UAV operations. The solution is implemented on top of the Etheruem platform and verified using four different smart contract verification tools. We also provided a security and cost analysis of our solution. For reproducibility, we made our implementation publicly available on Github.
Kailei Tang, Zhiyan Dong, Tianlun Dai, Zhongxue Gan
The issues of managing swarm intelligence are essential to many multiple tasks. The scenarios are complex and dynamic, which is hard for a single agent to satisfy the needs of various tasks. As thus, a practical intelligence cooperative combat scheme, composed of multiple agents, is required to supply a effective and efficient consensus for swarm intelligence with external conditions evolving. Among this scheme, the accuracy of information sharing, transmission, and the integrity of the stored data are all critically significant. The Blockchain, a digital distributed ledger,is distributed on different nodes, and each node holds the same data, which attracts increasing attentions recently. There are many consensus algorithms which is the key part of the blockchain, such as PoW, PoS, DPoS, PoR, etc. However, no matter in terms of performance, security and stability, existing work can hardly support a battle plan oriented to swarm intelligence. To our knowledge, there is no consensus algorithm that takes into account the resources of agent in swarm intelligence collaboration. Therefore, we introduce an optimization of DPoS for swarm intelligence based on agent behavior monitoring and agent’s own resource analysis (Delegated Proof of Stake based node’s Behavior and Resource, DPoSBR). Combining the situation of malicious behaviors of the agent and the resources of the agent, we choose the more trustworthy agent as the captain. Therefore, the captain agent is more secure and the election process is fairer. Finally, the extensive simulations are conducted to evaluate the performance of DPoSBR algorithm, which has good practicability. Meanwhile, it enables more agents to participate, which is beneficial to the decentralization of the system and can promote the enthusiasm of the entire agents, and it prevents the malicious agents from doing malicious behaviors again.
Gang Li, Bin He, Zhipeng Wang, Xu Cheng · 5 authors
Wireless sensor networks (WSNs) are widely used in the field of monitoring. For data collection of sensor nodes in large-scale monitoring scenarios, unmanned aerial vehicle (UAV)-assisted WSNs have emerged. For the security and validity of data collection, a blockchain-enhanced data collection framework for UAV-assisted WSNs is presented in this article. To reduce data redundancy in WSNs, a sparsity-optimized and compressed sensing-based spatiotemporal data aggregation model is built. A UAV identity authentication mechanism based on a Merkle tree is also designed to ensure the security of data transmission. By combining blockchain building and data aggregation, a disaster semantic blockchain (DSB) based on a data reconstruction-directed consensus mechanism is presented. Disaster semantics are extracted by analyzing the semantic association relationship of disaster, background, event, and sensor data. The experimental results show that the blockchain-enhanced spatiotemporal data aggregation effectively increases the network life cycle and data reconstruction accuracy. The disaster situation can be described accurately through the DSB.
The integration of air and ground smart vehicles is becoming a new paradigm of future transportation. A decent number of smart unmanned vehicles or UAS will be sharing the national airspace for various purposes, such as express delivery, surveillance, etc. However, the proliferation of UAS also brings challenges considering the safe integration of them into the current Air Traffic Management (ATM) systems. Especially when the current Automatic Dependent Surveillance Broadcasting (ADS-B) systems do not have message authentication mechanisms, it can not distinguish whether an authorized UAS is using the corresponding airspace. In this paper, we aim to address these practical challenges in two folds. We first use blockchain to provide a secure authentication platform for flight plan approval and sharing between the existing ATM facilities. We then use the fountain code to encode the authentication payloads and adapt them into the de facto communication protocol of ATM. This maintains backward compatibility and ensures the verification success rate under the noisy broadcasting channel. We simulate the realistic wireless communication scenarios and theoretically prove that our proposed authentication framework is with low latency and highly compatible with existing ATM communication protocols.
Reliable and flexible emergency networks are of paramount essence for disaster relief during or after the event of disasters due to the destruction or lack of terrestrial communication infrastructures. Thanks to fast deployment and flexible mobilities, unmanned aerial vehicles (UAVs) emerge as a promising paradigm to efficiently establish emergency networks and perform immediate disaster relief tasks in affected areas. However, in such UAV-assisted disaster relief networks (UDRNs), the limited onboard batteries and computational capacities of UAVs hinder them from performing computation-intensive missions. Moreover, critical security vulnerabilities arise in data transmission among UAVs owing to the untrusted environment, open communication channels, and unreliable misbehavior tracing. To this end, this article investigates UDRNs based on blockchain and machine learning to achieve secure and efficient data transmission. Specifically, we first present a lightweight blockchain-enabled collaborative aerial-ground networking framework to safeguard data delivery under disasters, where a credit-based delegated proof-of-stake consensus protocol is further devised to enhance consensus efficiency while promoting UAVs' honest behaviors. In addition, by harnessing the idle computing power of ground vehicles (referred to as vehicular fog computing), a novel reinforcement learning-based algorithm is developed to intelligently offload UAVs' computation missions to the moving vehicles in the dynamic environment. Experimental results demonstrate that the proposed framework outperforms the existing approaches, in terms of consensus security, user utility, task latency, and energy consumption. Finally, future research directions in this emerging area are discussed.
While 5G can facilitate high-speed Internet access and make over-the-horizon control a reality for unmanned aerial vehicles (UAVs; also known as drones), there are also potential security and privacy considerations, for example, authentication among drones. Centralized authentication approaches not only suffer from a single point of failure but they are also incapable of cross-domain authentication. This complicates the cooperation of drones from different domains. To address these limitations, a blockchain-based cross-domain authentication scheme for intelligent 5G-enabled Internet of drones is proposed in this article. Our approach employs multiple signatures based on threshold sharing to build an identity federation for collaborative domains. This allows us to support domain joining and exiting. Reliable communication between cross-domain devices is achieved by utilizing smart contract for authentication. The session keys are negotiated to secure subsequent communication between two parties. Our security and performance evaluations show that the proposed scheme is resistant to common attacks targeting Internet of Things (IoT) devices (including drones), as well as demonstrating its effectiveness and efficiency.