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Towards Inference of DDoS Mitigation Rules

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F22%3A10133463" target="_blank" >RIV/63839172:_____/22:10133463 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/9789798" target="_blank" >https://ieeexplore.ieee.org/document/9789798</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/NOMS54207.2022.9789798" target="_blank" >10.1109/NOMS54207.2022.9789798</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Towards Inference of DDoS Mitigation Rules

  • Original language description

    DDoS attacks still represent a severe threat to network services. While there are more or less workable solutions to defend against these attacks, there is a significant space for further research regarding automation of reactions and subsequent management. In this paper, we focus on one piece of the whole puzzle. We strive to automatically infer filtering rules which are specific to the current DoS attack to decrease the time to mitigation. We employ a machine learning technique to create a model of the traffic mix based on observing network traffic during the attack and normal period. The model is converted into the filtering rules. We evaluate our approach with various setups of hyperparameters. The results of our experiments show that the proposed approach is feasible in terms of the capability of inferring successful filtering rules.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/VI20192022137" target="_blank" >VI20192022137: Adaptive protection against DDoS attacks</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022

  • ISBN

    978-1-66540-601-7

  • ISSN

    2374-9709

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    1-5

  • Publisher name

    Institute of Electrical and Electronics Engineers Inc.

  • Place of publication

    Budapest, Hungary

  • Event location

    Budapest, Hungary

  • Event date

    Apr 25, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000851572700054