Blockchain-Empowered Immutable and Reliable Delivery Service (BIRDS) Using UAV Networks
- URL: http://arxiv.org/abs/2403.12060v1
- Date: Wed, 7 Feb 2024 12:39:59 GMT
- Title: Blockchain-Empowered Immutable and Reliable Delivery Service (BIRDS) Using UAV Networks
- Authors: Sana Hafeez, Habib Ullah Manzoor, Lina Mohjazi, Ahmed Zoha, Muhammad Ali Imran, Yao Sun,
- Abstract summary: Exploiting unmanned aerial vehicles (UAVs) for delivery services is expected to reduce delivery time and human resource costs.
The proximity of these UAVs to the ground can make them an ideal target for opportunistic criminals.
We propose the blockchain-Empowered, Immutable, and Reliable Delivery Service (BIRDS) framework to address data security challenges.
- Score: 6.66583575156837
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Exploiting unmanned aerial vehicles (UAVs) for delivery services is expected to reduce delivery time and human resource costs. However, the proximity of these UAVs to the ground can make them an ideal target for opportunistic criminals. Consequently, UAVs may be hacked, diverted from their destinations, or used for malicious purposes. Furthermore, as a decentralized (peer-to-peer) technology, the blockchain has immense potential to enable secure, decentralized, and cooperative communication among UAVs. With this goal in mind, we propose the Blockchain-Empowered, Immutable, and Reliable Delivery Service (BIRDS) framework to address data security challenges. BIRDS deploys communication hubs across a scalable network. Following the registration phase of BIRDS, UAV node selection is carried out based on a specific consensus proof-of-competence (PoC), where UAVs are evaluated solely on their credibility. The chosen finalist is awarded a certificate for the BIRDS global order fulfillment system. The simulation results demonstrate that BIRDS requires fewer UAVs compared to conventional solutions, resulting in reduced costs and emissions. The proposed BIRDS framework caters to the requirements of numerous users while necessitating less network traffic and consuming low energy.
Related papers
- BETA-UAV: Blockchain-based Efficient Authentication for Secure UAV Communication [6.885742280873289]
This paper presents an Efficient, and Trusted Authentication scheme for UAV communication, BETA-UAV.
The smart contract in BETA-UAV allows participants to publish and call transactions from the blockchain network.
transaction addresses are proof of freshness and trustworthiness for subsequent transmissions.
arXiv Detail & Related papers (2024-02-24T13:54:54Z) - A Blockchain-Enabled Framework of UAV Coordination for Post-Disaster Networks [7.249638174814088]
This paper presents a robust blockchain-enabled framework to securely coordinate UAV fleets for disaster response.
We make two key contributions: a consortium blockchain for secure and private multi-agency coordination; and an optimized consensus protocol balancing efficiency and fault tolerance.
Comprehensive simulations showcase the framework's ability to enhance transparency, automation, scalability, and cyber-attack resilience for UAV coordination in post-disaster networks.
arXiv Detail & Related papers (2024-02-23T14:01:27Z) - Graph Koopman Autoencoder for Predictive Covert Communication Against
UAV Surveillance [29.15836826461713]
Low Probability of Detection (LPD) communication aims to obscure the very presence of radio frequency (RF) signals.
Unmanned Aerial Vehicles (UAVs) can detect RF signals from the ground by hovering over specific areas of interest.
We introduce a novel framework that combines graph neural networks (GNN) with Koopman theory to predict the trajectories of multiple fixed-wing UAVs.
arXiv Detail & Related papers (2024-01-23T23:42:55Z) - Blockchain-Envisioned UAV-Aided Disaster Relief Networks: Challenges and Solutions [21.759507457111468]
Unmanned aerial vehicles (UAVs)-aided disaster relief networks (UDRNs) leverage UAVs to assist ground relief networks by swiftly assessing affected areas and timely delivering lifesaving supplies.
To meet the growing demands for collaborative, trust-free, and transparent UDRN services, blockchain-based UDRNs emerge as a promising approach through immutable ledgers and distributed smart contracts.
This paper presents potential solutions: (i) a series of collaborative smart contracts for coordinated relief management; (ii) a dynamic contract audit mechanism to prevent known/unknown contract vulnerabilities; and (iii) a robust transaction forensics strategy with on
arXiv Detail & Related papers (2023-10-08T14:32:25Z) - UAV Swarm-enabled Collaborative Secure Relay Communications with
Time-domain Colluding Eavesdropper [115.56455278813756]
Unmanned aerial vehicles (UAV) as aerial relays are practically appealing for assisting Internet Things (IoT) network.
In this work, we aim to utilize the UAV to assist secure communication between the UAV base station and terminal terminal devices.
arXiv Detail & Related papers (2023-10-03T11:47:01Z) - A Multi-UAV System for Exploration and Target Finding in Cluttered and
GPS-Denied Environments [68.31522961125589]
We propose a framework for a team of UAVs to cooperatively explore and find a target in complex GPS-denied environments with obstacles.
The team of UAVs autonomously navigates, explores, detects, and finds the target in a cluttered environment with a known map.
Results indicate that the proposed multi-UAV system has improvements in terms of time-cost, the proportion of search area surveyed, as well as successful rates for search and rescue missions.
arXiv Detail & Related papers (2021-07-19T12:54:04Z) - 3D UAV Trajectory and Data Collection Optimisation via Deep
Reinforcement Learning [75.78929539923749]
Unmanned aerial vehicles (UAVs) are now beginning to be deployed for enhancing the network performance and coverage in wireless communication.
It is challenging to obtain an optimal resource allocation scheme for the UAV-assisted Internet of Things (IoT)
In this paper, we design a new UAV-assisted IoT systems relying on the shortest flight path of the UAVs while maximising the amount of data collected from IoT devices.
arXiv Detail & Related papers (2021-06-06T14:08:41Z) - Efficient UAV Trajectory-Planning using Economic Reinforcement Learning [65.91405908268662]
We introduce REPlanner, a novel reinforcement learning algorithm inspired by economic transactions to distribute tasks between UAVs.
We formulate the path planning problem as a multi-agent economic game, where agents can cooperate and compete for resources.
As the system computes task distributions via UAV cooperation, it is highly resilient to any change in the swarm size.
arXiv Detail & Related papers (2021-03-03T20:54:19Z) - Privacy-Preserving Federated Learning for UAV-Enabled Networks:
Learning-Based Joint Scheduling and Resource Management [45.15174235000158]
Unmanned aerial vehicles (UAVs) are capable of serving as flying base stations (BSs) for supporting data collection, artificial intelligence (AI) model training, and wireless communications.
It is impractical to send raw data of devices to UAV servers for model training.
In this paper, we develop an asynchronous federated learning framework for multi-UAV-enabled networks.
arXiv Detail & Related papers (2020-11-28T18:58:34Z) - Artificial Intelligence for UAV-enabled Wireless Networks: A Survey [72.10851256475742]
Unmanned aerial vehicles (UAVs) are considered as one of the promising technologies for the next-generation wireless communication networks.
Artificial intelligence (AI) is growing rapidly nowadays and has been very successful.
We provide a comprehensive overview of some potential applications of AI in UAV-based networks.
arXiv Detail & Related papers (2020-09-24T07:11:31Z) - Artificial Intelligence Aided Next-Generation Networks Relying on UAVs [140.42435857856455]
Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aided next-generation networking is proposed for dynamic environments.
In the AI-enabled UAV-aided wireless networks (UAWN), multiple UAVs are employed as aerial base stations, which are capable of rapidly adapting to the dynamic environment.
As a benefit of the AI framework, several challenges of conventional UAWN may be circumvented, leading to enhanced network performance, improved reliability and agile adaptivity.
arXiv Detail & Related papers (2020-01-28T15:10:22Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.