物联网设备分类技术与流量分析综述

Swati Shivkumar Shriyal, B. Ainapure
{"title":"物联网设备分类技术与流量分析综述","authors":"Swati Shivkumar Shriyal, B. Ainapure","doi":"10.1109/ICTAI53825.2021.9673420","DOIUrl":null,"url":null,"abstract":"Classification of IOT devices is a trending topic nowadays. Gartner predicted that there will be 25 billion Internet of Things (IOT) devices in use. There is an increase in the risk of security breaches for devices connected to the internet, because of the proliferation of smart devices. To identify the malfunction of the devices, it is very important to identify every device connected to the network. There are some basic techniques that were traditionally used to classify the device connected to the network; they are port-based and payload-based. Today machine learning techniques are widely used as it gives more accuracy for identifying devices. The classification of IOT devices is still an immature topic, as many researchers have noted was the classification of network traffic. This article, look at emerging trends to classify IOT devices using various techniques. Also, the performance and accuracy of the various techniques used until now is discussed. This paper highlights the security issues for devices connected to the network. Finally, a discussion on an emerging subject is done, i.e. using Blockchain with IOT to secure communication between different IOT devices.","PeriodicalId":278263,"journal":{"name":"2021 International Conference on Technological Advancements and Innovations (ICTAI)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"IoT Device Classification Techniques and Traffic Analysis - A Review\",\"authors\":\"Swati Shivkumar Shriyal, B. Ainapure\",\"doi\":\"10.1109/ICTAI53825.2021.9673420\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Classification of IOT devices is a trending topic nowadays. Gartner predicted that there will be 25 billion Internet of Things (IOT) devices in use. There is an increase in the risk of security breaches for devices connected to the internet, because of the proliferation of smart devices. To identify the malfunction of the devices, it is very important to identify every device connected to the network. There are some basic techniques that were traditionally used to classify the device connected to the network; they are port-based and payload-based. Today machine learning techniques are widely used as it gives more accuracy for identifying devices. The classification of IOT devices is still an immature topic, as many researchers have noted was the classification of network traffic. This article, look at emerging trends to classify IOT devices using various techniques. Also, the performance and accuracy of the various techniques used until now is discussed. This paper highlights the security issues for devices connected to the network. Finally, a discussion on an emerging subject is done, i.e. using Blockchain with IOT to secure communication between different IOT devices.\",\"PeriodicalId\":278263,\"journal\":{\"name\":\"2021 International Conference on Technological Advancements and Innovations (ICTAI)\",\"volume\":\"103 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Technological Advancements and Innovations (ICTAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTAI53825.2021.9673420\",\"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 International Conference on Technological Advancements and Innovations (ICTAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTAI53825.2021.9673420","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

物联网设备的分类是当今的一个热门话题。高德纳预测,全球将有250亿个物联网(IOT)设备投入使用。由于智能设备的普及,连接到互联网的设备出现安全漏洞的风险有所增加。为了识别设备的故障,识别连接到网络的每个设备是非常重要的。传统上,有一些基本技术用于对连接到网络的设备进行分类;它们是基于端口和基于有效负载的。今天,机器学习技术被广泛使用,因为它可以更准确地识别设备。物联网设备的分类仍然是一个不成熟的话题,正如许多研究人员所指出的那样,网络流量的分类。本文将介绍使用各种技术对物联网设备进行分类的新兴趋势。此外,还讨论了迄今为止使用的各种技术的性能和准确性。本文重点介绍了连接到网络的设备的安全问题。最后,对一个新兴主题进行了讨论,即使用区块链与物联网来保护不同物联网设备之间的通信。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IoT Device Classification Techniques and Traffic Analysis - A Review
Classification of IOT devices is a trending topic nowadays. Gartner predicted that there will be 25 billion Internet of Things (IOT) devices in use. There is an increase in the risk of security breaches for devices connected to the internet, because of the proliferation of smart devices. To identify the malfunction of the devices, it is very important to identify every device connected to the network. There are some basic techniques that were traditionally used to classify the device connected to the network; they are port-based and payload-based. Today machine learning techniques are widely used as it gives more accuracy for identifying devices. The classification of IOT devices is still an immature topic, as many researchers have noted was the classification of network traffic. This article, look at emerging trends to classify IOT devices using various techniques. Also, the performance and accuracy of the various techniques used until now is discussed. This paper highlights the security issues for devices connected to the network. Finally, a discussion on an emerging subject is done, i.e. using Blockchain with IOT to secure communication between different IOT devices.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信