Autors: Ivanova, D. A., Borovska, P. I.
Title: In silico knowledge data discovery in the context of IoT ecosystem security issues
Keywords: In Silico Knowledge Data Discovery, IoT Ecosystem Security

Abstract: In this paper we have analyzed the IoT security issues in the context of security intelligence and IoT analytics. Furthermore, the potential and benefits of applying Big data technologies have been revealed for building up intelligent security solutions for the IoT ecosystem. We have suggested design approach for building up parallel differentiated diagnostic analytic workflows for the case study of intrusion detection. The conceptual software architecture of intelligent intrusion detection system has been proposed comprising machine learning and operational sections. The functionality of the intelligent system involves detection of unknown attacks based on models and identification of known attacks based on sets of rules. The functionality of the proposed intelligent system has been verified experimentally for the case study of diagnostics.



    AIP Conference Proceedings, vol. 2333, issue 3000, 2021, United States, AIP,

    Copyright AIP

    Цитирания (Citation/s):
    1. Afzal, S., Faisal, A., Siddique, I., & Afzal, M. Internet of Things (IoT) Security: Issues, Challenges and Solutions. - 2021 - от чужди автори в чужди издания, неиндексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus