The rise of traffic classification in IoT networks: A survey. (15th March 2020)

• Record Type: Journal Article
• Authors: Tahaei, Hamid; Afifi, Firdaus; Asemi, Adeleh; Zaki, Faiz; Anuar, Nor Badrul
• Is Part Of: Journal of network and computer applications. Volume 154(2020)
• Publication Date: 2020-03-15
• Subjects: Internet of things -- IoT traffic classification -- Traffic analysis -- IoT security -- M2M traffic classification; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2020.102538
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: With the proliferation of the Internet of Things (IoT), the integration and communication of various objects have become a prevalent practice. The huge growth of IoT devices and different characteristics in the IoT traffic patterns have brought attention to traffic classification methods to address various raised issues in IoT applications. While network traffic classification has been well discussed in a number of surveys and review papers, it is still immature in IoT due to the differences in traffic characteristics in IoT and Non-IoT devices. This survey looks at the emerging trends of network traffic classification in IoT and the utilization of traffic classification in its applications. It also compares the legacy of traffic classification methods and presents an overview of traditional models. This paper extends the discussion with a taxonomy of the current network traffic classification within the IoT context. We then expose commercial and real-world use cases of the IoT traffic classification and finally outline open research issues and challenges in this domain.