Traffic trace engineering

Pham Van Dung, Marat Zhanikeev, Yoshiaki Tanaka

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Traffic traces captured from backbone links have been widely used in traffic analysis for many years. By far the most popular use of such traces is replay where conditions and states of the original traffic trace are recreated almost identically in simulation or emulation environments. When the end target of such research is detection of traffic anomalies, it is crucial that some anomalies are found in the trace in the first place. Traces with many real-life anomalies are rare, however. This paper pioneers a new area of research where traffic traces are engineered to contain traffic anomalies as per user request. The method itself is non-intrusive by retaining the IP address space found in the original trace. Engineering of several popular anomalies are shown in the paper while the method is flexible enough to accommodate any level of traffic trace engineering in the future.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages1-10
    Number of pages10
    Volume5787 LNCS
    DOIs
    Publication statusPublished - 2009
    Event12th Asia-Pacific Network Operations and Management Symposium, APNOMS 2009 - Jeju
    Duration: 2009 Sep 232009 Sep 25

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume5787 LNCS
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other12th Asia-Pacific Network Operations and Management Symposium, APNOMS 2009
    CityJeju
    Period09/9/2309/9/25

    Fingerprint

    Trace
    Traffic
    Engineering
    Anomaly
    Traffic Analysis
    Emulation
    Backbone
    Target
    Simulation

    Keywords

    • Analysis
    • Anomaly
    • Emulation
    • Replay
    • Simulation
    • Trace
    • Traffic

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

    Cite this

    Van Dung, P., Zhanikeev, M., & Tanaka, Y. (2009). Traffic trace engineering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5787 LNCS, pp. 1-10). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5787 LNCS). https://doi.org/10.1007/978-3-642-04492-2_1

    Traffic trace engineering. / Van Dung, Pham; Zhanikeev, Marat; Tanaka, Yoshiaki.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5787 LNCS 2009. p. 1-10 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5787 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Van Dung, P, Zhanikeev, M & Tanaka, Y 2009, Traffic trace engineering. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5787 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5787 LNCS, pp. 1-10, 12th Asia-Pacific Network Operations and Management Symposium, APNOMS 2009, Jeju, 09/9/23. https://doi.org/10.1007/978-3-642-04492-2_1
    Van Dung P, Zhanikeev M, Tanaka Y. Traffic trace engineering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5787 LNCS. 2009. p. 1-10. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-04492-2_1
    Van Dung, Pham ; Zhanikeev, Marat ; Tanaka, Yoshiaki. / Traffic trace engineering. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5787 LNCS 2009. pp. 1-10 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
    @inproceedings{cbaec516c04c42fbb625637aa6161009,
    title = "Traffic trace engineering",
    abstract = "Traffic traces captured from backbone links have been widely used in traffic analysis for many years. By far the most popular use of such traces is replay where conditions and states of the original traffic trace are recreated almost identically in simulation or emulation environments. When the end target of such research is detection of traffic anomalies, it is crucial that some anomalies are found in the trace in the first place. Traces with many real-life anomalies are rare, however. This paper pioneers a new area of research where traffic traces are engineered to contain traffic anomalies as per user request. The method itself is non-intrusive by retaining the IP address space found in the original trace. Engineering of several popular anomalies are shown in the paper while the method is flexible enough to accommodate any level of traffic trace engineering in the future.",
    keywords = "Analysis, Anomaly, Emulation, Replay, Simulation, Trace, Traffic",
    author = "{Van Dung}, Pham and Marat Zhanikeev and Yoshiaki Tanaka",
    year = "2009",
    doi = "10.1007/978-3-642-04492-2_1",
    language = "English",
    isbn = "3642044913",
    volume = "5787 LNCS",
    series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
    pages = "1--10",
    booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

    }

    TY - GEN

    T1 - Traffic trace engineering

    AU - Van Dung, Pham

    AU - Zhanikeev, Marat

    AU - Tanaka, Yoshiaki

    PY - 2009

    Y1 - 2009

    N2 - Traffic traces captured from backbone links have been widely used in traffic analysis for many years. By far the most popular use of such traces is replay where conditions and states of the original traffic trace are recreated almost identically in simulation or emulation environments. When the end target of such research is detection of traffic anomalies, it is crucial that some anomalies are found in the trace in the first place. Traces with many real-life anomalies are rare, however. This paper pioneers a new area of research where traffic traces are engineered to contain traffic anomalies as per user request. The method itself is non-intrusive by retaining the IP address space found in the original trace. Engineering of several popular anomalies are shown in the paper while the method is flexible enough to accommodate any level of traffic trace engineering in the future.

    AB - Traffic traces captured from backbone links have been widely used in traffic analysis for many years. By far the most popular use of such traces is replay where conditions and states of the original traffic trace are recreated almost identically in simulation or emulation environments. When the end target of such research is detection of traffic anomalies, it is crucial that some anomalies are found in the trace in the first place. Traces with many real-life anomalies are rare, however. This paper pioneers a new area of research where traffic traces are engineered to contain traffic anomalies as per user request. The method itself is non-intrusive by retaining the IP address space found in the original trace. Engineering of several popular anomalies are shown in the paper while the method is flexible enough to accommodate any level of traffic trace engineering in the future.

    KW - Analysis

    KW - Anomaly

    KW - Emulation

    KW - Replay

    KW - Simulation

    KW - Trace

    KW - Traffic

    UR - http://www.scopus.com/inward/record.url?scp=70350462943&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=70350462943&partnerID=8YFLogxK

    U2 - 10.1007/978-3-642-04492-2_1

    DO - 10.1007/978-3-642-04492-2_1

    M3 - Conference contribution

    AN - SCOPUS:70350462943

    SN - 3642044913

    SN - 9783642044915

    VL - 5787 LNCS

    T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

    SP - 1

    EP - 10

    BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

    ER -