{"title":"智能环境下物联网流量的实证研究:特征、研究差距与建议","authors":"M. Sneh, A. Bhandari","doi":"10.1109/SMART52563.2021.9676298","DOIUrl":null,"url":null,"abstract":"Adopting the Internet of Things (IoT) in multi-functional domains has led to management, operational, and security challenges. As a foundation stone, researchers have invested sincere efforts towards classifying traffic, thereby categorizing the devices. However, the classification solutions are missing the vital attributes of the state-of-the-art high-performance real-time framework. This paper provides the taxonomy of the techno-functional application areas of the IoT characterization. The article also inferences empirically investigated IoT traffic attributes leveraging an Australian dataset collected from 28 IoT devices over six months. Based on the forensics of IoT traffic, the characteristics of IoT-based traffic are listed, which paves the grounds of the security, operational, and management solutions for IoT devices. The paper also details the research gaps in the implemented solutions by exploring additional research dimensions of a trailblazing real-time classification solution, which the researchers often ignore. Lastly, the paper offers recommendations and prospects.","PeriodicalId":356096,"journal":{"name":"2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Empirical Investigation of IoT Traffic in Smart Environments: Characteristics, Research Gaps and Recommendations\",\"authors\":\"M. Sneh, A. Bhandari\",\"doi\":\"10.1109/SMART52563.2021.9676298\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Adopting the Internet of Things (IoT) in multi-functional domains has led to management, operational, and security challenges. As a foundation stone, researchers have invested sincere efforts towards classifying traffic, thereby categorizing the devices. However, the classification solutions are missing the vital attributes of the state-of-the-art high-performance real-time framework. This paper provides the taxonomy of the techno-functional application areas of the IoT characterization. The article also inferences empirically investigated IoT traffic attributes leveraging an Australian dataset collected from 28 IoT devices over six months. Based on the forensics of IoT traffic, the characteristics of IoT-based traffic are listed, which paves the grounds of the security, operational, and management solutions for IoT devices. The paper also details the research gaps in the implemented solutions by exploring additional research dimensions of a trailblazing real-time classification solution, which the researchers often ignore. Lastly, the paper offers recommendations and prospects.\",\"PeriodicalId\":356096,\"journal\":{\"name\":\"2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMART52563.2021.9676298\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMART52563.2021.9676298","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Empirical Investigation of IoT Traffic in Smart Environments: Characteristics, Research Gaps and Recommendations
Adopting the Internet of Things (IoT) in multi-functional domains has led to management, operational, and security challenges. As a foundation stone, researchers have invested sincere efforts towards classifying traffic, thereby categorizing the devices. However, the classification solutions are missing the vital attributes of the state-of-the-art high-performance real-time framework. This paper provides the taxonomy of the techno-functional application areas of the IoT characterization. The article also inferences empirically investigated IoT traffic attributes leveraging an Australian dataset collected from 28 IoT devices over six months. Based on the forensics of IoT traffic, the characteristics of IoT-based traffic are listed, which paves the grounds of the security, operational, and management solutions for IoT devices. The paper also details the research gaps in the implemented solutions by exploring additional research dimensions of a trailblazing real-time classification solution, which the researchers often ignore. Lastly, the paper offers recommendations and prospects.