Bozorgchenani, A. orcid.org/0000-0003-1360-6952, Zarakovitis, C.C., Chien, S.F. et al. (4 more authors) (2022) Joint Security-vs-QoS Framework: Optimizing the Selection of Intrusion Detection Mechanisms in 5G networks. In: Proceedings of the 17th International Conference on Availability, Reliability and Security. ARES 2022: The 17th International Conference on Availability, Reliability and Security, 23-26 Aug 2023, Vienna, Austria. ACM ISBN 9781450396707
Abstract
The advent of 5G technology introduces new - and potentially undiscovered - cybersecurity challenges, with unforeseen impacts on our economy, society, and environment. Interestingly, Intrusion Detection Mechanisms (IDMs) can provide the necessary network monitoring to ensure - to a big extent - the detection of 5G-related cyberattacks. Yet, how to realize the attack surface of 5G networks with respect to the detected risks, and, consequently, how to optimize the cybersecurity levels of the network, remains an open critical challenge. In respect, this work focuses on deploying multiple distributed Security Agents (SAs) that can run different IDMs over various network components and proposes a cybersecurity mechanism for optimizing the network’s attack surface with respect to the Quality of Service (QoS). The proposed approach relies on a new closed-form utility function to describe the trade-off between cybersecurity and QoS and uses multi-objective optimization to improve the selection of each SA detection level. We demonstrate via simulations that before optimization, an increase in the detection level of SAs brings a direct decrease in QoS as more computational, bandwidth and monetary resources are utilized for IDM processing. Thereby, after optimization, we demonstrate that our mechanism can strike a balance between cybersecurity and QoS while showcasing the impact of the importance of different objectives of the joint optimization.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © ACM 2022. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ARES '22: Proceedings of the 17th International Conference on Availability, Reliability and Security, https://doi.org/10.1145/3538969.3544480. |
Keywords: | 5G, cybersecurity, system cost, QoS, multi-objective-optimization, risk detection, risk mitigation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 26 Jan 2024 10:46 |
Last Modified: | 31 Jan 2024 15:36 |
Published Version: | https://dl.acm.org/doi/10.1145/3538969.3544480 |
Status: | Published |
Publisher: | ACM |
Identification Number: | 10.1145/3538969.3544480 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:208276 |