Decoding 5G security: toward a hybrid threat ontology

Author:

Paskauskas R. AndrewORCID

Abstract

The rapid deployment of 5G technology ushers in a new era of connectivity with unparalleled potential, but it also presents unprecedented security challenges. A meticulous review of ENISA's Taxonomy is undertaken, specifically in its application to 5G networks and their cybersecurity assets. This work also evaluates the relevance of cybersecurity structures in other EU papers and ENISA reports, providing critical insights into the evolving landscape of cybersecurity. In the context of hybrid threats, the study categorizes these multifaceted challenges using the established taxonomy. It establishes connections between ontological categories, thereby deriving an ontology that illuminates the intricate nature of hybrid threats within 5G. The integration of the 5G vision with the TEN-T initiative for trans-European transport corridors constitutes a significant part of the research. This phase incorporates a comprehensive review of the Connecting Europe Facility (CEF) work plan, encompassing vital elements like Multi-Access Edge Computing (MEC), Network Function Virtualization (NFV), Software-Defined Networking (SDN), FOG/EDGE/CLOUD computing. The study also delves into the intricacies of 5G cybersecurity, examining ENISA's contributions to 5G network security and risk while navigating the landscape of applicable EU and national laws, along with EU guidance. This exploration extends to cybersecurity implications within the context of the CEF funding program. Significantly, the integration of RDF coding plays a pivotal role in aligning the developed ontology with the JRC Cybersecurity Taxonomy. This exposition represents a milestone in the field of 5G cybersecurity, as it effectively aligns a comprehensive ontology, designed to comprehend and mitigate hybrid threats in 5G networks, with the JRC Cybersecurity Taxonomy. The alignment is achieved by leveraging RDF coding techniques, which have greatly enhanced the ontology's machine-readability and interoperability.

Funder

Horizon 2020 Framework Programme

Publisher

F1000 Research Ltd

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3