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Analysis for the adoption of security standards to improve the management of securities in public organizations

  • Segundo Moisés Toapanta Toapanta
  • , Madeleine Lilibeth Alvarado Ronquillo
  • , Luis Enrique Mafla Gallegos
  • , Alberto Ochoa Zezzatti

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Public organizations have the ongoing task of properly managing the security of the information they handle. The objective of this research is to analyze the security standards adopted by public organizations in Ecuador to improve their management of information security. The deductive method was applied for the review and analysis of appropriate standards for public institutions. As a result, information was obtained on the different security policies, standards and guidelines that apply, national and international public organizations. A Diagram of activities for the adoption of standards for public organizations resulted; a prototype standards-based Information Security Management Model; and an Information Security Management Matrix, from which the Risk Mitigation Percentage was calculated. It was concluded that maintaining high levels of security in public organizations requires the adoption of control standards in different areas and the collaboration of the different organizational and hierarchical levels of public organizations.

    Original languageEnglish
    Title of host publicationMachine Learning and Artificial Intelligence - Proceedings of MLIS 2020
    EditorsAntonio J. Tallon-Ballesteros, Chi-Hua Chen
    PublisherIOS Press BV
    Pages310-321
    Number of pages12
    ISBN (Electronic)9781643681368
    DOIs
    StatePublished - 2 Dec 2020
    Event2020 International Conference on Machine Learning and Intelligent Systems, MLIS 2020 - Virtual, Online, Korea, Republic of
    Duration: 25 Oct 202028 Oct 2020

    Publication series

    NameFrontiers in Artificial Intelligence and Applications
    Volume332
    ISSN (Print)0922-6389
    ISSN (Electronic)1879-8314

    Conference

    Conference2020 International Conference on Machine Learning and Intelligent Systems, MLIS 2020
    Country/TerritoryKorea, Republic of
    CityVirtual, Online
    Period25/10/2028/10/20

    Bibliographical note

    Publisher Copyright:
    © 2020 The authors and IOS Press.

    Keywords

    • Information security
    • Public organization
    • Security management
    • Security standards

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