Blockchain Technology Used for Smart Drone Swarms: History
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Contributor:
Athanasios Koulianos
,
Antonios Litke

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. The concept of leveraging blockchain technology to address problems with identification, security, and storage in UAV clusters is not new. There have been many approaches that have used novel methods to examine how we can use the benefits of blockchain technology to lessen these issues.

  • IoT
  • drone swarms

1. Introduction

Drone swarms have gained a lot of traction in recent years for use in military applications thanks to their versatility in a range of tasks, including search and rescue operations, surveillance, reconnaissance, and more. These missions do, of course, have their limitations. Research has been conducted to identify the best solution to NP-hard problems like path planning and obstacle avoidance using swarm intelligence algorithms [1][2][3]. A detailed study on swarm intelligence and its role in UAV systems through a layered approach can be found in [4]. In addition to these problems, safeguarding the communications of these unmanned aerial vehicle systems is the key challenge people must overcome. Drones in a swarm have to communicate between them in order to efficiently coordinate their actions. However, there might be obstructions that prevent them from communicating, either naturally (like obstacles) or artificially (like cyberattacks) or because of poor network coverage in some places. The security of these technologies, as an issue, cannot be ignored. Cyber attacks are known to be susceptible to drones [5]. A successful attack on one drone could have severe effects on the entire mission. Furthermore, if the communication links are insecure and the data are not encrypted, an attacker might very simply acquire vital military data, exposing entire operations and endangering lives.
Another significant challenge with drone swarms is the problem of trust. A seamless and effective operation is facilitated by mutual trust among swarm members. Drones should put their trust in the other swarm members and make sure they behave properly and by the rules. On the other hand, drones may behave dishonestly or fail to make effective decisions, which could, at best, lead to mission failure. A comprehensive review of these issues and the solutions researchers created to overcome them can be found in [6].
One of these solutions relies on the use of blockchains. Blockchain technology is an innovative and promising idea that can offer solutions to various problems in different sectors, including the defense industry. Its undisputed, unmodifiable, and fully transparent environment in terms of transactions is attracting more and more users every day.
Since its inception, researchers have focused their attention on the technology that underlies blockchains with the goal of employing it outside the finance industry. Works related to blockchains, as well as the areas they focus on, can be found in [7][8][9]. Applications of blockchains in the Internet of Things (IoT), storage and data transfer, network security, and data privacy are some of the modern issues that concern researchers worldwide. Therefore, blockchains find applications in businesses, governments, the health sector, and even the military due to the security and transparency they offer. This technology is especially appealing to the military, where data and communication security are crucial.
Research into the use of blockchain technology in drone swarms has huge implications for various industries and fields, including military, commercial, and political applications. Improved security, privacy, and trust among members, as well as better coordination and performance, are potential benefits of such systems. These studies may consequently result in a rise in the use and creation of technologies that alter how tasks like disaster relief and surveillance are carried out. In terms of ethical, legal, and social problems, research on blockchain technology and its use in the military operations of UAV squadrons in sensitive, high-risk areas is extremely important. For instance, the employment of autonomous drone swarms in military operations raises concerns about accountability and transparency in the decision-making process, the protection of human rights, and the risk of civilian casualties [10][11]. Researchers can contribute to the creation of a more safe, open, and moral drone swarm system whose advantages will be distributed in a just and equitable way by finding solutions to these problems. In order to shape the future of these technologies and their impact on society, as well as address some of the most pressing problems facing us today, research into the uses of blockchain technology in swarms of drones is, therefore, of utmost importance.

2. Blockchain Technology Used for Smart Drone Swarms

The concept of leveraging blockchain technology to address problems with identification, security, and storage in UAV clusters is not new. There have been studies that have used novel methods to examine how people can use the benefits of blockchain technology to lessen these issues.
A more theoretical prospect of blockchain applications in UAV swarms can be found in [12][13][14]. A detailed explanation of how blockchain technology can be applied to drone clusters through various scenarios and examples is provided. Also, a thorough examination of the advantages of applying blockchain technology to these systems is conducted. Moreover, the potential problems and limitations of such applications are described. Works with specific results and contributions related to the technical aspects of this area are presented below.
For example, in [15], a lightweight blockchain is proposed, along with an interesting mechanism for message routing between UAV nodes to enhance the security of routing in 5G NR cellular networks. In addition, a way of identifying and managing malicious nodes is included. Proof of Traffic (PoT) is utilized for reaching a consensus, while the synchronization of the updated blocks is performed passively within the energy consumption limits. As it is based on the results of this work, the proposed scheme is very efficient and capable of ensuring the smooth operation of the swarm, even if there are malicious intruders inside it.
A novel approach in which a UAV swarm is able to conduct surveillance missions at specific points of interest (POIs) by utilizing blockchain technology is proposed in [16]. It is essentially a tangled-based model (IOTA), which relies on a decision-making strategy (smart contract) for the coordination of UAVs. The described idea is based on autonomous swarm operation (without the existence of some control center), in contrast to most of the published research. The blockchain is embedded in the UAVs, while there are some more nodes on the ground that have specific functionalities (route planning, financial transactions).
The UAV-TIEN system is a blockchain-based data transmission model proposed in [17]. This specific scheme is secure due to the nature of blockchain technology and also robust against line-of-sight blocking problems. Monte Carlo simulations were carried out in order to evaluate the efficiency of the proposed model. The results were very promising due to the model’s ability to increase the data broadcasting range. Scalability-related issues may arise due to the broadcasting mechanism that was used in the study (broadcasting to every UAV inside the range). However, by selecting a different mechanism and utilizing some ground station nodes, this problem can be solved. Also, by optimizing parameters such as the maximum blockchain length (MBL) and broadcasting frequency (BF), channel congestion can be improved.
In order to ensure security in UAV networks during surveillance and identify potentially compromised UAVs based on trust policies, [18] suggests a method that utilizes blockchain principles. The method allows for the accurate detection of false data when an official UAV is compromised. To validate the suggested strategy, ABS-SecurityUAV, a unique agent-based simulator, was employed. In the conducted tests, the majority of the UAVs were able to confirm information about a person moving through a regulated area, and none of them confirmed false information from a UAV that had been hijacked.
In [19], a blockchain-based data acquisition procedure is shown in which data are collected from loTs utilizing a UAV as a relay and securely stored in a blockchain on an MEC (Mobile Edge Computing) server. Data are encrypted using the proposed technique before being sent to the MEC server with the help of a UAV. The public key of the UAV is used to execute encryption, while the private key of the loID is used to establish a signature when transferring data from loIDs. After decrypting the data, the UAV checks the identity of the loID using an 𝜂-hash bloom filter. The MEC server verifies the data and the sender’s identity after receiving it. After successful validation and after receiving approval from the validators, the data are stored in the blockchain. A security study is conducted to demonstrate the viability of the suggested secure solution. The effectiveness of the suggested strategy is assessed using MATLAB R2023b simulations and practical applications, with some extremely encouraging outcomes.
Additionally, very few studies have been conducted to assess the functionalities of proposed models through real-world tests and simulations. Also, the majority of relevant publications have overlooked the importance of the leader’s security in such systems. In order to address this gap, an innovative, lightweight, and easy-to-deploy smart contract is proposed in this work, in which a new leader-election mechanism is introduced. A realistic simulation that combines blockchain technology and actual drone programming tools was used to test this work’s findings. The simulation results were very promising, and this work could potentially be used as a starting point to create state-of-the-art drone systems with enhanced security and an improved decision-making process.

This entry is adapted from the peer-reviewed paper 10.3390/fi15100344

References

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  2. Liu, H.; Chen, Q.; Pan, N.; Sun, Y.; Yang, Y. Three-Dimensional Mountain Complex Terrain and Heterogeneous Multi-UAV Cooperative Combat Mission Planning. IEEE Access 2020, 8, 197407–197419.
  3. Arafat, M.Y.; Moh, S. Localization and clustering based on swarm intelligence in UAV networks for emergency communications. IEEE Internet Things J. 2019, 6, 8958–8976.
  4. Zhou, Y.; Rao, B.; Wang, W. UAV swarm intelligence: Recent advances and future trends. IEEE Access 2020, 8, 183856–183878.
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  9. Taylor, P.J.; Dargahi, T.; Dehghantanha, A.; Parizi, R.M.; Choo, K.K.R. A systematic literature review of blockchain cyber security. Digit. Commun. Netw. 2020, 6, 147–156.
  10. Konert, A.; Balcerzak, T. Military autonomous drones (UAVs)-from fantasy to reality. Legal and Ethical implications. Transp. Res. Procedia 2021, 59, 292–299.
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  12. Castelló Ferrer, E. The blockchain: A new framework for robotic swarm systems. In Proceedings of the Future Technologies Conference, Vancouver, BC, Canada, 15–16 November 2018.
  13. Kuzmin, A.; Znak, E. Blockchain-base structures for a secure and operate network of semi-autonomous unmanned aerial vehicles. In Proceedings of the IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), Singapore, 31 July–2 August 2018.
  14. Hafeez, S.; Khan, A.R.; Al-Quraan, M.; Mohjazi, L.; Zoha, A.; Imran, M.A.; Sun, Y. Blockchain-Assisted UAV Communication Systems: A Comprehensive Survey. IEEE Open J. Veh. Technol. 2023, 4, 558–580.
  15. Wang, J.; Liu, Y.; Niu, S.; Song, H. Lightweight blockchain assisted secure routing of swarm UAS networking. Comput. Commun. 2021, 165, 131–140.
  16. Santos de Campos, M.G.; Chanel, C.P.; Chauffaut, C.; Lacan, J. Towards a blockchain-based multi-uav surveillance system. Front. Robot. AI 2021, 8, 557692.
  17. Chao, H.; Maheshwari, A.; Sudarsanan, V.; Tamaskar, S.; DeLaurentis, D.A. UAV traffic information exchange network. In Proceedings of the Aviation Technology, Integration, and Operations Conference, Atlanta, GA, USA, 25–29 June 2018.
  18. García-Magariño, I.; Lacuesta, R.; Rajarajan, M.; Lloret, J. Security in networks of unmanned aerial vehicles for surveillance with an agent-based approach inspired by the principles of blockchain. Ad Hoc Netw. 2019, 86, 72–82.
  19. Islam, A.; Shin, S.Y. BUAV: A blockchain based secure UAV-assisted data acquisition scheme in Internet of Things. J. Commun. Netw. 2019, 21, 491–502.
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