All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Time series dataset for network security situational awareness

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F25%3A10133784" target="_blank" >RIV/63839172:_____/25:10133784 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S2352340925010996" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2352340925010996</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.dib.2025.112386" target="_blank" >10.1016/j.dib.2025.112386</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Time series dataset for network security situational awareness

  • Original language description

    In the field of network security situational awareness (NSSA), it is challenging to find a usable dataset. Most of the datasets used in existing research papers are outdated, small, publicly unavailable due to the private infrastructure on which they were created, or unusable for other reasons. This paper presents a new dataset derived from a well-documented and substantial source, suitable for use with neural networks that require larger datasets than classical machine learning approaches. This dataset can help the research community in various ways. The dataset consists of four parts, each containing the time series generated from cybersecurity alerts collected between 2017 and 2018 and between 2023 and 2024. Alerts were collected from the Warden system, which collects and shares information about security events detected by various security systems across multiple organizations. These are data whose labeling is performed by the detection system itself (silver standard). In total, about three billion alerts were collected and processed to time series.

  • 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

    <a href="/en/project/LM2023054" target="_blank" >LM2023054: e-Infrastructure CZ</a><br>

  • Continuities

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

Others

  • Publication year

    2025

  • 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

    64

  • Issue of the periodical within the volume

    nečíslováno

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    17

  • Pages from-to

    nestránkováno

  • UT code for WoS article

    001663507600010

  • EID of the result in the Scopus database

    2-s2.0-105025653296