Active Learning for Network Traffic Classification: A Technical Study

Shahraki A, Abbasi M, Taherkordi A, Jurcut AD (2022)

Publication Type: Journal article

Publication year: 2022

Journal

IEEE Transactions on Cognitive Communications and Networking IEEE

Book Volume: 8

Pages Range: 422-439

Journal Issue: 1

DOI: 10.1109/TCCN.2021.3119062

Abstract

Network Traffic Classification (NTC) has become an important feature in various network management operations, e.g., Quality of Service (QoS) provisioning and security services. Machine Learning (ML) algorithms as a popular approach for NTC can promise reasonable accuracy in classification and deal with encrypted traffic. However, ML-based NTC techniques suffer from the shortage of labeled traffic data which is the case in many real-world applications. This study investigates the applicability of an active form of ML, called Active Learning (AL), in NTC. AL reduces the need for a large number of labeled examples by actively choosing the instances that should be labeled. The study first provides an overview of NTC and its fundamental challenges along with surveying the literature on ML-based NTC methods. Then, it introduces the concepts of AL, discusses it in the context of NTC, and review the literature in this field. Further, challenges and open issues in AL-based classification of network traffic are discussed. Moreover, as a technical survey, some experiments are conducted to show the broad applicability of AL in NTC. The simulation results show that AL can achieve high accuracy with a small amount of data.

Involved external institutions

Fraunhofer-Institut für Integrierte Schaltungen (IIS) DE Germany (DE) Free University of Bozen - Bolzano IT Italy (IT) University of Oslo NO Norway (NO) University College Dublin (UCD) IE Ireland (IE)

How to cite

APA:

Shahraki, A., Abbasi, M., Taherkordi, A., & Jurcut, A.D. (2022). Active Learning for Network Traffic Classification: A Technical Study. IEEE Transactions on Cognitive Communications and Networking, 8(1), 422-439. https://dx.doi.org/10.1109/TCCN.2021.3119062

MLA:

Shahraki, Amin, et al. "Active Learning for Network Traffic Classification: A Technical Study." IEEE Transactions on Cognitive Communications and Networking 8.1 (2022): 422-439.

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