{"title":"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","authors":"Lobna Osman","doi":"10.54216/jcim.090203","DOIUrl":null,"url":null,"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.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Intelligent Spatial Military Intrusion Detection using Reactive Mobility Unmanned Vehicles Based on IoT and metaheuristic Optimization Algorithm\",\"authors\":\"Lobna Osman\",\"doi\":\"10.54216/jcim.090203\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":169383,\"journal\":{\"name\":\"Journal of Cybersecurity and Information Management\",\"volume\":\"2015 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cybersecurity and Information Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54216/jcim.090203\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cybersecurity and Information Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54216/jcim.090203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Intelligent Spatial Military Intrusion Detection using Reactive Mobility Unmanned Vehicles Based on IoT and metaheuristic Optimization Algorithm
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.