Applications and use cases of multilevel granularity for network traffic classification
Document Type
Conference Item
Publication Date
1-1-2020
Abstract
Network traffic classification is a fundamental process in network management and security. It allows network administrators to classify traffic based on various levels of classification granularity such as the source type or application. Existing literature focuses on analyzing the entire network traffic classification process with emphasis on the classification techniques. However, besides classification techniques, the literature lacks coverage on classification granularity, which deserves proper attention due to its increasing application in modern networks. Understanding the various levels of classification granularity and their use cases allow for more optimized traffic classification. As such, this paper aims to explore the different levels of classification granularity and their use cases. We studied papers published between 2013 and 2019 in order to investigate the different levels of granularity and use cases in the literature. As a result, this paper groups the classification granularity into a systematic multilevel taxonomy to assist in attaining a deeper understanding of their applications. Finally, to motivate future research, we elaborated on the current challenges and future directions for network traffic classification.
Keywords
Network traffic classification, Granularity, Network management, Network monitoring
Divisions
Computer
Funders
Ministry of Education, Malaysia under Fundamental Research Grant Scheme (FRGS/1/2018/ICT03/UM/02/3)
Publisher
IEEE
Publisher Location
345 E 47TH ST, NEW YORK, NY 10017 USA
Event Title
2020 16TH IEEE International Colloquium on Signal Processing & Its Applications (CSPA 2020)
Event Location
Langkawi, Kedah, Malaysia
Event Dates
28-29 February 2020
Event Type
conference
Additional Information
16th IEEE International Colloquium on Signal Processing and its Applications (CSPA), Langkawi, MALAYSIA, FEB 28-29, 2020