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CopAS: A Big Data Forensic Analytics System

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00130487" target="_blank" >RIV/00216224:14330/23:00130487 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scitepress.org/PublicationsDetail.aspx?ID=umluZcUjShA=&t=1" target="_blank" >https://www.scitepress.org/PublicationsDetail.aspx?ID=umluZcUjShA=&t=1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.5220/0011929000003482" target="_blank" >10.5220/0011929000003482</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    CopAS: A Big Data Forensic Analytics System

  • Original language description

    With the advancing digitization of our society, network security has become one of the critical concerns for most organizations. In this paper, we present CopAS, a system targeted at Big Data forensics analysis, allowing network operators to comfortably analyze and correlate large amounts of network data to get insights about potentially malicious and suspicious events. We demonstrate the practical usage of CopAS for insider attack detection on a publicly available PCAP dataset and show how the system can be used to detect insiders hiding their malicious activity in the large amounts of data streams generated during the operations of an organization within the network.

  • 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/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

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

    Proceedings of the 8th International Conference on Internet of Things, Big Data and Security IoTBDS - Volume 1

  • ISBN

    9789897586439

  • ISSN

    2184-4976

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    150-161

  • Publisher name

    SciTePress

  • Place of publication

    Setubal, Portugal

  • Event location

    Prague, Czech Republic

  • Event date

    Jan 1, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001078900300014