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A DTW Approach for Complex Data A Case Study with Network Data Streams

Published: 07 June 2023 Publication History

Abstract

Dynamic Time Warping (DTW) is a robust method to measure the similarity between two sequences. This paper proposes a method based on DTW to analyse high-speed data streams. The central idea is to decompose the network traffic into sequences of histograms of packet sizes and then calculate the distance between pairs of such sequences using DTW with Kullback-Leibler (KL) distance. As a baseline, we also compute the Euclidean Distance between the sequences of histograms. Since our preliminary experiments indicate that the distance between two sequences falls within a different range of values for distinct types of streams, we then exploit this distance information for stream classification using a Random Forest. The approach was investigated using recent internet traffic data from a telecommunications company. To illustrate the application of our approach, we conducted a case study with encrypted Internet Protocol Television (IPTV) network traffic data. The goal was to use our DTW-based approach to detect the video codec used in the streams, as well as the IPTV channel. Results strongly suggest that the DTW distance value between the data streams is highly informative for such classification tasks.

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Cited By

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  • (2024)Enhanced Design of a Tai Chi Teaching Assistance System Integrating DTW Algorithm and SVMICST Transactions on Scalable Information Systems10.4108/eetsis.577111:5Online publication date: 2-May-2024
  • (2024)A Link-Quality Anomaly Detection Framework for Software-Defined Wireless Mesh NetworksIEEE Transactions on Machine Learning in Communications and Networking10.1109/TMLCN.2024.33889732(495-510)Online publication date: 2024
  • (2024)Exploring Dynamic Time Warping for Network Traffic Analysis2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)10.1109/ICOCWC60930.2024.10470894(1-6)Online publication date: 29-Jan-2024

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  1. A DTW Approach for Complex Data A Case Study with Network Data Streams

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    cover image ACM Conferences
    SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing
    March 2023
    1932 pages
    ISBN:9781450395175
    DOI:10.1145/3555776
    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: 07 June 2023

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    Author Tags

    1. dynamic time warping
    2. network data streams
    3. traffic analysis

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    Cited By

    View all
    • (2024)Enhanced Design of a Tai Chi Teaching Assistance System Integrating DTW Algorithm and SVMICST Transactions on Scalable Information Systems10.4108/eetsis.577111:5Online publication date: 2-May-2024
    • (2024)A Link-Quality Anomaly Detection Framework for Software-Defined Wireless Mesh NetworksIEEE Transactions on Machine Learning in Communications and Networking10.1109/TMLCN.2024.33889732(495-510)Online publication date: 2024
    • (2024)Exploring Dynamic Time Warping for Network Traffic Analysis2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)10.1109/ICOCWC60930.2024.10470894(1-6)Online publication date: 29-Jan-2024

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