Susanto , D. Stiawan, Dian Palupi Rini, M. Arifin, Mohd Yazid Bin Idris, Nizar Alsharif, R. Budiarto
{"title":"Dimensional Reduction With Fast ICA for IoT Botnet Detection","authors":"Susanto , D. Stiawan, Dian Palupi Rini, M. Arifin, Mohd Yazid Bin Idris, Nizar Alsharif, R. Budiarto","doi":"10.1080/19361610.2022.2079906","DOIUrl":null,"url":null,"abstract":"Abstract The Internet of Things (IoT) has unique characteristics with a minimalist design and has network access with great scalability, which makes it difficult to control access. Setting up an intrusion detection system (IDS) on an IoT system while taking into account its unique characteristics is a big challenge. In this paper, we propose a dimensional reduction approach utilizing the fast independent component analysis (ICA) method to address scalability issues of IDS for IoT systems. Experimental results show that the reduction of dimensions by the fast ICA method overall improves the IDS execution time and does not significantly affect accuracy.","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":"18 1","pages":"665 - 688"},"PeriodicalIF":1.1000,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Security Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/19361610.2022.2079906","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CRIMINOLOGY & PENOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract The Internet of Things (IoT) has unique characteristics with a minimalist design and has network access with great scalability, which makes it difficult to control access. Setting up an intrusion detection system (IDS) on an IoT system while taking into account its unique characteristics is a big challenge. In this paper, we propose a dimensional reduction approach utilizing the fast independent component analysis (ICA) method to address scalability issues of IDS for IoT systems. Experimental results show that the reduction of dimensions by the fast ICA method overall improves the IDS execution time and does not significantly affect accuracy.
物联网(Internet of Things, IoT)具有极简设计的独特特点,其网络接入具有极大的可扩展性,使得接入控制变得困难。在物联网系统上设置入侵检测系统(IDS),同时考虑到其独特的特性是一项巨大的挑战。在本文中,我们提出了一种利用快速独立分量分析(ICA)方法来解决物联网系统IDS的可扩展性问题的降维方法。实验结果表明,快速ICA方法的降维总体上提高了IDS的执行时间,且对准确率没有显著影响。