Insiders Detection in the Uncertain IoD using Fuzzy Logic

Sihem Benfriha, Nabila Labraoui
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引用次数: 1

Abstract

Unmanned aerial vehicles (UAVs) and various network entities deployed on the ground can communicate with each other over the Internet of Drones (IoD), a network architecture designed expressly to allow communications between heterogenous entities. Drone technology has a wide range of uses, including on-demand package delivery, traffic and wild life surveillance, inspection of infrastructure and search, rescue and agriculture. However, IoD systems are vulnerable to numerous attacks, The main goal is to develop an all-encompassing security model that can be used to analyze security concerns in various UAV-based systems. With exceptional flexibility and increasing efficiency, trust management is a promising alternative to traditional detection methods. In a heterogeneous environment, it is also compatible with other security mechanisms. In this article, we present a fuzzy logic as an Insider Detection technique which calculate sensor data trust and assessing node behavior. To build confidence throughout the entire IoD, our proposal divides trust into two parts: Data trust and Node trust. This is in contrast to earlier models. Experimental results show that our solution is effective in terms of False positive ratio and Average of end-to-end delay.
基于模糊逻辑的不确定IoD内部人员检测
无人机(uav)和部署在地面上的各种网络实体可以通过无人机互联网(IoD)相互通信,IoD是一种专门设计用于允许异质实体之间通信的网络架构。无人机技术有广泛的用途,包括按需包裹递送、交通和野生动物监控、基础设施检查、搜索、救援和农业。然而,IoD系统容易受到多种攻击,主要目标是开发一个包罗万象的安全模型,可用于分析各种基于无人机的系统中的安全问题。信任管理具有出色的灵活性和不断提高的效率,是传统检测方法的一个有希望的替代方案。在异构环境中,它还与其他安全机制兼容。在本文中,我们提出了一种模糊逻辑作为内部检测技术来计算传感器数据信任和评估节点行为。为了在整个IoD中建立信任,我们的建议将信任分为两部分:数据信任和节点信任。这与早期的模型形成了对比。实验结果表明,该方法在误报率和端到端平均延迟方面是有效的。
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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