An Intelligent Spatial Military Intrusion Detection using Reactive Mobility Unmanned Vehicles Based on IoT and metaheuristic Optimization Algorithm

Lobna Osman
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Abstract

One of the most significant uses of the Internet of Things is military infiltration detection (IoT). Autonomous drones play a major role in IoT-based vulnerability scanning (UVs). By relocating UVs remotely, this work introduces a new algorithm called the Moth-Flame Optimization Algorithm (MFO). In particular, MFO is used to proactively manage UVs under various scenarios and under different intrusion-covering situations. According to actual studies, the suggested algorithm is both profitable and efficient.
基于物联网和元启发式优化算法的被动机动无人车空间军事入侵智能检测
物联网最重要的用途之一是军事渗透检测(IoT)。自主无人机在基于物联网的漏洞扫描(UVs)中发挥着重要作用。通过对紫外线进行远程定位,本文提出了一种新的蛾焰优化算法(MFO)。特别是,MFO可以在不同的场景和不同的入侵覆盖情况下对uv进行主动管理。实际研究表明,本文提出的算法是有效的。
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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CiteScore
0.70
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