{"title":"利用人工智能和机器学习方法的混合特征缩减技术检测无线传感器网络中的网络攻击","authors":"Mohamed H. Behiry, Mohammed Aly","doi":"10.1186/s40537-023-00870-w","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":15158,"journal":{"name":"Journal of Big Data","volume":"30 4","pages":"1-39"},"PeriodicalIF":8.6000,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cyberattack detection in wireless sensor networks using a hybrid feature reduction technique with AI and machine learning methods\",\"authors\":\"Mohamed H. Behiry, Mohammed Aly\",\"doi\":\"10.1186/s40537-023-00870-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":15158,\"journal\":{\"name\":\"Journal of Big Data\",\"volume\":\"30 4\",\"pages\":\"1-39\"},\"PeriodicalIF\":8.6000,\"publicationDate\":\"2024-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Big Data\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1186/s40537-023-00870-w\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Big Data","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1186/s40537-023-00870-w","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
期刊介绍:
The Journal of Big Data publishes high-quality, scholarly research papers, methodologies, and case studies covering a broad spectrum of topics, from big data analytics to data-intensive computing and all applications of big data research. It addresses challenges facing big data today and in the future, including data capture and storage, search, sharing, analytics, technologies, visualization, architectures, data mining, machine learning, cloud computing, distributed systems, and scalable storage. The journal serves as a seminal source of innovative material for academic researchers and practitioners alike.