A trust-based mechanism for drones in smart cities

IF 2.1 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Geetanjali Rathee, Akshay Kumar, Chaker Abdelaziz Kerrache, Razi Iqbal
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引用次数: 1

Abstract

Smart cities equipped with intelligent devices can enhance the lifestyle and quality of humans by automatically and collaboratively acting as a sustainable resource to the ecosystem. In addition, the technological advancement can be further empowered by interconnecting various types of technologies, such as IoT, Artificial Intelligence, drones and robotics which will clearly improve the Quality of Services, energy efficiency and connectivity to the overall system. The integration of drones hovering over smart cities with the other devices in the smart city network brings a lot of benefits. However, it can also lead to various security and privacy concerns in the network. The aim of this article is to put forward a secure and safe smart city communication environment by proposing a trust establishment scheme for the ad hoc Unmanned Aerial Vehicles network. In which, malicious devices can be traced and blocked by analysing and evaluating their historical interactions within the system and calculating their trust values. A behaviour-based and local trust value scheme is used to analyse the trust of each communicating device that is further associated with a blockchain distributed ledger. The proposed mechanism is measured over various networking and security metrics, including throughput, latency, accuracy and block updating compared to the existing state-of-the-art solutions.

Abstract Image

智能城市中无人机的信任机制
配备智能设备的智慧城市可以通过自动协作作为生态系统的可持续资源来提高人类的生活方式和质量。此外,通过互联各种技术,如物联网、人工智能、无人机和机器人技术,可以进一步推动技术进步,这将明显提高服务质量、能源效率和整个系统的连通性。在智慧城市上空盘旋的无人机与智慧城市网络中的其他设备的融合带来了很多好处。然而,它也可能导致网络中的各种安全和隐私问题。本文的目的是通过提出一种自组网无人机网络信任建立方案,构建一个安全可靠的智慧城市通信环境。其中,可以通过分析和评估恶意设备在系统内的历史交互并计算其信任值来跟踪和阻止恶意设备。使用基于行为的本地信任值方案来分析与区块链分布式账本进一步关联的每个通信设备的信任。与现有的最先进的解决方案相比,所提议的机制通过各种网络和安全指标进行测量,包括吞吐量、延迟、准确性和块更新。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IET Smart Cities
IET Smart Cities Social Sciences-Urban Studies
CiteScore
7.70
自引率
3.20%
发文量
25
审稿时长
21 weeks
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