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A Solution to Combat Cybersecurity Threats Involving Big Data Analytics in the Hadoop Ecosystem

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F17%3A39910615" target="_blank" >RIV/00216275:25410/17:39910615 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Solution to Combat Cybersecurity Threats Involving Big Data Analytics in the Hadoop Ecosystem

  • Original language description

    Information and data security have become the biggest concern for almost all organizations. At the same time, new security challenges emerge constantly as networks become more highly distributed and virtualization architectures are adopted. Big data analytics promises to deliver opportunities for prevention and detection of advanced cyberattacks using internal and external big security data. The increase of these streamed and stored data together with the development of distributed analytical systems has led to rapid increase in demand for big data analytics integration in in the field of cybersecurity. Therefore, this paper attempted to discuss these practices. A literature review was conducted and the most suitable components were identified with the aim to propose a conceptual model, which should help to combat cybersecurity threats involving big data analytics in the Hadoop ecosystem. By implementing this model, organizations may be able to detect threats, create more defense mechanisms, and improve security of their infrastructure.

  • 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

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2017

  • 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 30th International Business Information Management Association Conference

  • ISBN

    978-0-9860419-9-0

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    9

  • Pages from-to

    "1804 "- 1812

  • Publisher name

    International Business Information Management Association-IBIMA

  • Place of publication

    Norristown

  • Event location

    Madrid

  • Event date

    Nov 8, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000443640501052