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https://doi.org/10.21256/zhaw-29467| Publication type: | Conference paper |
| Type of review: | Peer review (publication) |
| Title: | MERLINS : moving target defense enhanced with deep-RL for NFV in-depth security |
| Authors: | Soussi, Wissem Christopoulou, Maria Gür, Gürkan Stiller, Burkhard |
| et. al: | No |
| DOI: | 10.1109/NFV-SDN59219.2023.10329594 10.21256/zhaw-29467 |
| Proceedings: | 2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) |
| Page(s): | 65 |
| Pages to: | 71 |
| Conference details: | 9th IEEE Conference on Network Functions Virtualization and Software-Defined Networking (NFV-SDN), Dresden, Germany, 7-9 November 2023 |
| Issue Date: | 2023 |
| Publisher / Ed. Institution: | IEEE |
| ISBN: | 979-8-3503-0254-7 |
| Language: | English |
| Subjects: | Moving target defense (MTD); 5G and Beyond 5G; NFV security management; Deep reinforcement learning |
| Subject (DDC): | 004: Computer science |
| Abstract: | Moving to a multi-cloud environment and service-based architecture, 5G and future 6G networks require additional defensive mechanisms to protect virtualized network resources. This paper presents MERLINS, a novel architecture generating optimal Moving Target Defense (MTD) policies for proactive and reactive security of network slices. By formally modeling telecommunication networks compliant with Network Function Virtualization (NFV) into a multi-objective Markov Decision Process (MOMDP), MERLINS uses deep Reinforcement Learning (deep-RL) to optimize the MTD strategy that considers security, network performance, and service level requirements. Practical experiments on a 5G testbed showcase the feasibility as well as restrictions of MTD operations and the effectiveness in mitigating malware infections. It is observed that multi-objective RL (MORL) algorithms outperform state-of-the-art deep-RL algorithms that scalarize the reward vector of the MOMDP. This improvement by a factor of two leads to a better MTD policy than the baseline static counterpart used for the evaluation. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/29467 |
| Fulltext version: | Accepted version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Computer Science (InIT) |
| Appears in collections: | Publikationen School of Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2023_Soussi-etal_MERLINS-NFV-security_IEEESDNNFV.pdf | Accepted Version | 4.91 MB | Adobe PDF |  View/Open |
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Soussi, W., Christopoulou, M., Gür, G., & Stiller, B. (2023). MERLINS : moving target defense enhanced with deep-RL for NFV in-depth security [Conference paper]. 2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), 65–71. https://doi.org/10.1109/NFV-SDN59219.2023.10329594
Soussi, W. et al. (2023) ‘MERLINS : moving target defense enhanced with deep-RL for NFV in-depth security’, in 2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN). IEEE, pp. 65–71. Available at: https://doi.org/10.1109/NFV-SDN59219.2023.10329594.
W. Soussi, M. Christopoulou, G. Gür, and B. Stiller, “MERLINS : moving target defense enhanced with deep-RL for NFV in-depth security,” in 2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), 2023, pp. 65–71. doi: 10.1109/NFV-SDN59219.2023.10329594.
SOUSSI, Wissem, Maria CHRISTOPOULOU, Gürkan GÜR und Burkhard STILLER, 2023. MERLINS : moving target defense enhanced with deep-RL for NFV in-depth security. In: 2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN). Conference paper. IEEE. 2023. S. 65–71. ISBN 979-8-3503-0254-7
Soussi, Wissem, Maria Christopoulou, Gürkan Gür, and Burkhard Stiller. 2023. “MERLINS : Moving Target Defense Enhanced with Deep-RL for NFV In-Depth Security.” Conference paper. In 2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), 65–71. IEEE. https://doi.org/10.1109/NFV-SDN59219.2023.10329594.
Soussi, Wissem, et al. “MERLINS : Moving Target Defense Enhanced with Deep-RL for NFV In-Depth Security.” 2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), IEEE, 2023, pp. 65–71, https://doi.org/10.1109/NFV-SDN59219.2023.10329594.
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