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Hornet 40: Network Dataset of Geographically Placed Honeypots

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00354948" target="_blank" >RIV/68407700:21230/22:00354948 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1016/j.dib.2022.107795" target="_blank" >https://doi.org/10.1016/j.dib.2022.107795</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.dib.2022.107795" target="_blank" >10.1016/j.dib.2022.107795</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Hornet 40: Network Dataset of Geographically Placed Honeypots

  • Original language description

    Deception technologies, and honeypots in particular, have been used for decades to understand how cyber attacks and attackers work. A myriad of factors impact the effectiveness of a honeypot. However, very few is known about the impact of the geographical location of honeypots on the amount and type of attacks. Hornet 40 is the first dataset designed to help understand how the geolocation of honeypots may impact the inflow of network attacks. The data consists of network flows in binary and text format, with up to 118 features, including 480 bytes of the content of each flow. They were created using the Argus flow collector. The passive honeypots are IP addresses connected to the Internet and do not have any honeypot software running, so attacks are not interactive. The data was collected from identically configured honeypot servers in eight locations: Amsterdam, Bangalore, Frankfurt, London, New York, San Francisco, Singapore, and Toronto. The dataset contains over 4.7 million network flows collected during forty days throughout April, May, and June 2021.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • 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

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Data in Brief

  • ISSN

    2352-3409

  • e-ISSN

  • Volume of the periodical

    40

  • Issue of the periodical within the volume

    February

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    10

  • Pages from-to

    1-10

  • UT code for WoS article

    000787646200036

  • EID of the result in the Scopus database

    2-s2.0-85123934105