Network Traffic Characterization Using L-moment Ratio Diagrams

Mihaela I. Chidean, Javier Carmona-Murillo, Rune Hylsberg Jacobsen, Qi Zhang

    Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

    Abstract

    5G networks are facing to new challenges related to the growing traffic volume and service diversity. Some of the major concerns in this new scenario are the security and privacy issues required for a full technology adoption. Traffic characterization is a compound of strategies intended to define formally the behaviour and patterns in the Internet traffic.In this work, we propose the use of statistical features of network flows to characterize some of the most common attacks in the current networks through the L-moment ratio diagrams. Our work identify the parameters that can discriminate normal from malicious traffic. Moreover, our preliminary results show that this technique enables the differentiation of anomalies and can also identify several types of attack traffic.

    Original languageEnglish
    Title of host publication2019 6th International Conference on Internet of Things : Systems, Management and Security, IOTSMS 2019
    Number of pages6
    PublisherIEEE
    Publication date2019
    Pages555-560
    Article number8939231
    ISBN (Electronic)978-1-7281-2949-5
    DOIs
    Publication statusPublished - 2019
    Event2019 Sixth International Conference on Internet of Things: Systems, Management and Security - Granada, Granada, Spain
    Duration: 22 Oct 201925 Oct 2019
    https://emergingtechnet.org/IOTSMS2019/

    Conference

    Conference2019 Sixth International Conference on Internet of Things: Systems, Management and Security
    LocationGranada
    Country/TerritorySpain
    CityGranada
    Period22/10/201925/10/2019
    Internet address

    Keywords

    • 5G
    • L-moment.
    • Network Traffic
    • Security

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