Jinsi Jose, Deepa V. Jose, Karna Srinivasa Rao, Justin Janz
{"title":"Impact of Machine Learning Algorithms in Intrusion Detection Systems for Internet of Things","authors":"Jinsi Jose, Deepa V. Jose, Karna Srinivasa Rao, Justin Janz","doi":"10.1109/ICACC-202152719.2021.9708404","DOIUrl":null,"url":null,"abstract":"The importance of security aspects is increased recently due to the enormous usage of IoT devices. Securing the system from all sorts of vulnerabilities is inevitable to use IoT applications. Intrusion detection systems are power mechanism which provides this service. The introduction of artificial intelligence into intrusion detection systems can further enhance its power. This paper is an attempt to understand the impact of machine learning algorithms in attack detection. Using the UNSW-NB 15 dataset, the impact of different machine learning algorithms is assessed.","PeriodicalId":198810,"journal":{"name":"2021 International Conference on Advances in Computing and Communications (ICACC)","volume":"78 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Advances in Computing and Communications (ICACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACC-202152719.2021.9708404","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The importance of security aspects is increased recently due to the enormous usage of IoT devices. Securing the system from all sorts of vulnerabilities is inevitable to use IoT applications. Intrusion detection systems are power mechanism which provides this service. The introduction of artificial intelligence into intrusion detection systems can further enhance its power. This paper is an attempt to understand the impact of machine learning algorithms in attack detection. Using the UNSW-NB 15 dataset, the impact of different machine learning algorithms is assessed.