research-article

Towards a Profiling View for Unsupervised Traffic Classification by Exploring the Statistic Features and Link Patterns

Authors:

Gong ZhangAuthors Info & Claims

NetAI'19: Proceedings of the 2019 Workshop on Network Meets AI & ML

Pages 50 - 56

https://doi.org/10.1145/3341216.3342213

Published: 14 August 2019 Publication History

Abstract

In this paper, we study the network traffic classification task. Different from existing supervised methods that rely heavily on the labeled statistic features in a long period (e.g., several hours or days), we adopt a novel view of unsupervised profiling to explore the flow features and link patterns in a short time window (e.g., several seconds), dealing with the zero-day traffic problem. Concretely, we formulate the traffic identification task as a graph co-clustering problem with topology and edge attributes, and proposed a novel Hybrid Flow Clustering (HFC) model. The model can potentially achieve high classification performance, since it comprehensively leverages the available information of both features and linkage. Moreover, the two information sources integrated in HFC can also be utilized to generate the profiling for each flow category, helping to reveal the deep knowledge and semantics of network traffic. The effectiveness of the model is verified in the extensive experiments on several real datasets of various scenarios, where HFC achieves impressive results and presents powerful application ability.

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Cited By

Qin MZhang CGao YZhang WYeung DBaeza-Yates RBonchi F(2024)Pre-train and Refine: Towards Higher Efficiency in K-Agnostic Community Detection without Quality DegradationProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671686(2467-2478)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671686
Qin MZhang CBai BZhang GYeung D(2023)Towards a Better Tradeoff between Quality and Efficiency of Community Detection: An Inductive Embedding Method across GraphsACM Transactions on Knowledge Discovery from Data10.1145/359660517:9(1-34)Online publication date: 15-Jun-2023
https://dl.acm.org/doi/10.1145/3596605
Liu CWu PXu MYang YGeng N(2023)Scalable Deep Reinforcement Learning-Based Online Routing for Multi-Type Service RequirementsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2023.328465134:8(2337-2351)Online publication date: Aug-2023
https://doi.org/10.1109/TPDS.2023.3284651
Show More Cited By

Index Terms

Towards a Profiling View for Unsupervised Traffic Classification by Exploring the Statistic Features and Link Patterns
1. Information systems
  1. World Wide Web
    1. Web mining
      1. Traffic analysis
2. Mathematics of computing
  1. Discrete mathematics
    1. Graph theory
      1. Graph algorithms

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cover image ACM Conferences

NetAI'19: Proceedings of the 2019 Workshop on Network Meets AI & ML

August 2019

96 pages

ISBN:9781450368728

DOI:10.1145/3341216

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 August 2019

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Shenzhen Key Lab

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SIGCOMM '19

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SIGCOMM

SIGCOMM '19: ACM SIGCOMM 2019 Conference

August 23, 2019

Beijing, China

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NetAI'19 Paper Acceptance Rate 13 of 38 submissions, 34%;

Overall Acceptance Rate 13 of 38 submissions, 34%

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Cited By

Qin MZhang CGao YZhang WYeung DBaeza-Yates RBonchi F(2024)Pre-train and Refine: Towards Higher Efficiency in K-Agnostic Community Detection without Quality DegradationProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671686(2467-2478)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671686
Qin MZhang CBai BZhang GYeung D(2023)Towards a Better Tradeoff between Quality and Efficiency of Community Detection: An Inductive Embedding Method across GraphsACM Transactions on Knowledge Discovery from Data10.1145/359660517:9(1-34)Online publication date: 15-Jun-2023
https://dl.acm.org/doi/10.1145/3596605
Liu CWu PXu MYang YGeng N(2023)Scalable Deep Reinforcement Learning-Based Online Routing for Multi-Type Service RequirementsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2023.328465134:8(2337-2351)Online publication date: Aug-2023
https://doi.org/10.1109/TPDS.2023.3284651
Gao YQin MDing YZeng LZhang CZhang WHan WZhao RBai B(2023)RaftGP: Random Fast Graph Partitioning2023 IEEE High Performance Extreme Computing Conference (HPEC)10.1109/HPEC58863.2023.10363495(1-7)Online publication date: 25-Sep-2023
https://doi.org/10.1109/HPEC58863.2023.10363495
Wu HLi WChen XCheng GHu XZhuang Y(2023)Batch classifier with adaptive update for backbone traffic classificationComputer Communications10.1016/j.comcom.2023.02.013202:C(57-72)Online publication date: 15-Mar-2023
https://dl.acm.org/doi/10.1016/j.comcom.2023.02.013
Fu YLi XLi XZhao SWang F(2023)Clustering unknown network traffic with dual-path autoencoderNeural Computing and Applications10.1007/s00521-022-08138-9Online publication date: 7-Jan-2023
https://doi.org/10.1007/s00521-022-08138-9
Dhont MTsiporkova EBoeva V(2022)Performance Profiling of Operating Modes via Multi-view Analysis Using Non-negative Matrix FactorisationRecent Advancements in Multi-View Data Analytics10.1007/978-3-030-95239-6_11(289-316)Online publication date: 21-May-2022
https://doi.org/10.1007/978-3-030-95239-6_11
Wu HChen XCheng GHu XZhuang Y(2021)BCAC: Batch Classifier based on Agglomerative Clustering for traffic classification in a backbone network2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS)10.1109/IWQOS52092.2021.9521310(1-10)Online publication date: 25-Jun-2021
https://doi.org/10.1109/IWQOS52092.2021.9521310
Liu CXu MYang YGeng N(2021)DRL-OR: Deep Reinforcement Learning-based Online Routing for Multi-type Service RequirementsIEEE INFOCOM 2021 - IEEE Conference on Computer Communications10.1109/INFOCOM42981.2021.9488736(1-10)Online publication date: 10-May-2021
https://doi.org/10.1109/INFOCOM42981.2021.9488736
Li DYuan QLi TChen SYang J(2020)Cross-domain Network Traffic Classification Using Unsupervised Domain Adaptation2020 International Conference on Information Networking (ICOIN)10.1109/ICOIN48656.2020.9016470(245-250)Online publication date: Jan-2020
https://doi.org/10.1109/ICOIN48656.2020.9016470
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