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Look at my Network: An Insight into the ISP Backbone Traffic

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F23%3A10133628" target="_blank" >RIV/63839172:_____/23:10133628 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21240/23:00370580

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/10327823" target="_blank" >https://ieeexplore.ieee.org/document/10327823</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.23919/CNSM59352.2023.10327823" target="_blank" >10.23919/CNSM59352.2023.10327823</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Look at my Network: An Insight into the ISP Backbone Traffic

  • Original language description

    High-speed ISP networks provide several challenges that prevent the creation of long-term datasets for giving insight into the traffic. Currently, there are no publicly available long-term datasets capturing the entirety of high-speed ISP networks. Such networks are traditionally monitored using IP Flows, which provide enough high-level information about the situation in the network and support various use cases, such as the detection of outages or security threats. Even with this type of aggregation long-term datasets are very unpractical due to their size. The other problem is that flow monitoring comes with significant aggregation and common traffic statistics are brief and lack useful details and require further processing. This paper addresses these problems and presents a new long-term aggregated dataset, a detailed analysis of public network traffic measured on the ISP backbone, and a monitoring architecture composed of open-source tools capable of using an existing flow exporter infrastructure. Such insight into traffic helps to design and develop hardware optimizations, tuning the performance of monitoring systems, and adapting security detection algorithms.

  • 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/VJ02010024" target="_blank" >VJ02010024: Flow-based Encrypted Traffic Analysis</a><br>

  • Continuities

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

Others

  • Publication year

    2023

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2023 19th International Conference on Network and Service Management (CNSM)

  • ISBN

    978-3-903176-59-1

  • ISSN

    2165-963X

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

  • Publisher name

    IEEE

  • Place of publication

    New York

  • Event location

    Niagara Falls

  • Event date

    Oct 30, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article