Abstract
AbstractThe emergence of the Internet of Things (IoT) concept as a new direction of technological development raises new problems such as valid and timely identification of such devices, security vulnerabilities that can be exploited for malicious activities, and management of such devices. The communication of IoT devices generates traffic that has specific features and differences with respect to conventional devices. This research seeks to analyze the possibilities of applying such features for classifying devices, regardless of their functionality or purpose. This kind of classification is necessary for a dynamic and heterogeneous environment, such as a smart home where the number and types of devices grow daily. This research uses a total of 41 IoT devices. The logistic regression method enhanced by the concept of supervised machine learning (logitboost) was used for developing a classification model. Multiclass classification model was developed using 13 network traffic features generated by IoT devices. Research has shown that it is possible to classify devices into four previously defined classes with high performances and accuracy (99.79%) based on the traffic flow features of such devices. Model performance measures such as precision, F-measure, True Positive Ratio, False Positive Ratio and Kappa coefficient all show high results (0.997–0.999, 0.997–0.999, 0.997–0.999, 0–0.001 and 0.9973, respectively). Such a developed model can have its application as a foundation for monitoring and managing solutions of large and heterogeneous IoT environments such as Industrial IoT, smart home, and similar.
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Reference61 articles.
1. DigiCert Inc (2018) State of IoT Security Survey 2018. https://www.digicert.com/wp-content/uploads/2018/11/StateOfIoTSecurity_Report_11_02_18_F_am.pdf
Accessed 18 Mar 2020
2. Vodafone Business (2019) Your IoT-Driven Future [Internet] 2019. https://www.vodafone.com/business/news-and-insights/whitepaper/vodafone-iot-barometer-2019 Accessed 14 May 2020
3. Kejriwal S, Mahajan S (2016) Smart buildings: how IoT technology aims to add value for real estate companies. Deloitte University Press, London
4. HIS (2017) The Internet of Things : a movement, not a market Start revolutionizing the competitive landscape. IHS Markit. https://ihsmarkit.com/Info/1017/internet-of-things.html Accessed 21 Mar 2020
5. Adat V, Gupta BB (2018) Security in Internet of Things: issues, challenges, taxonomy, and architecture. Telecommunication Systems 67(3):423–441
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