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An Efficient and Provably Secure Certificateless Blind Signature Scheme for Flying Ad-Hoc Network Based on Multi-Access Edge Computing

机译:基于多访问边缘计算的飞行ad-hoc网络的高效且可证明的无证明盲签名方案

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摘要

Unmanned aerial vehicles (UAVs), when interconnected in a multi-hop ad-hoc fashion, or as a flying ad-hoc network (FANET), can efficiently accomplish mission-critical tasks. However, UAVs usually suffer from the issues of shorter lifespan and limited computational resources. Therefore, the existing security approaches, being fragile, are not capable of countering the attacks, whether known or unknown. Such a security lapse can result in a debilitated FANET system. In order to cope up with such attacks, various efficient signature schemes have been proposed. Unfortunately, none of the solutions work effectively because of incurred computational and communication costs. We aimed to resolve such issues by proposing a blind signature scheme in a certificateless setting. The scheme does not require public-key certificates, nor does it suffer from the key escrow problem. Moreover, the data that are aggregated from the platform that monitors the UAVs might be too huge to be processed by the same UAVs engaged in the monitoring task. Due to being latency-sensitive, it demands high computational capability. Luckily, the envisioned fifth generation (5G) mobile communication introduces multi-access edge computing (MEC) in its architecture. MEC, when incorporated in a UAV environment, in our proposed model, divides the workload between UAVs and the on-board microcomputer. Thus, our proposed model extends FANET to the 5G mobile network and enables a secure communication between UAVs and the base station (BS).
机译:无人驾驶飞行器(无人机),当以多跳ad-hoc时尚互连,或作为飞行的ad-hoc网络(FANET),可以有效地完成任务关键任务。然而,无人机通常遭受较短的寿命和有限的计算资源问题。因此,现有的安全方法是脆弱的,无论是已知还是未知的,都无法对抗攻击。这种安全失效可能导致欺保式粉丝系统。为了应对这种攻击,已经提出了各种有效的签名方案。不幸的是,由于所产生的计算和通信成本,这些解决方案都没有有效地工作。我们旨在通过在无证书设置中提出盲目签名方案来解决这些问题。该计划不需要公钥证书,它也不遭受关键托管问题。此外,从监视UVS的平台聚合的数据可能太大,无法通过从事监控任务的相同的UAV处理。由于延迟敏感,它需要高计算能力。幸运的是,设想的第五代(5G)移动通信在其体系结构中引入了多访问边缘计算(MEC)。 MEC,当在UAV环境中结合在我们提出的模型中,将工作负载划分为无人机和车载微计算机之间的工作量。因此,我们所提出的模型将FANET延伸到5G移动网络,并且可以在UAV和基站(BS)之间安全通信。

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