Topology-aware cognitive self-protection framework for automated detection and mitigation of security and privacy incidents in 5G-IoT networks

Pablo Benlloch-Caballero; Ignacio Sanchez-Navarro; Antonio Matencio-Escolar; Jose M. Alcaraz Calero; Qi Wang

doi:10.1109/ICNP59255.2023.10355595

Topology-aware cognitive self-protection framework for automated detection and mitigation of security and privacy incidents in 5G-IoT networks

Pablo Benlloch-Caballero^*, Ignacio Sanchez-Navarro, Antonio Matencio-Escolar, Jose M. Alcaraz Calero, Qi Wang

^*Corresponding author for this work

School of Computing, Engineering and Physical Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Internet of Things (IoT) coupled with 5G networks enable unprecedented levels of scalability and performance in the computing industry. These enhanced performance features allow to offer and deploy a wide range of new use cases and services in scenarios such as Smart Cities, Smart Grid or Industry 5.0 just to mention a few. However, the inherent complexity of such networks is a serious concern in terms of security. Furthermore, the vulnerability and low-power constraints of IoT devices make such networks a targeted vector for cyber criminals. In this contribution, authors present an innovative topology-aware Cognitive Self-protection framework able to detect and mitigate attacks in an autonomous way with no human intervention in the wired segments of 5G-IoT multi-tenant networks. Preliminary tests carried out on a realistic emulated testbed show promising results in terms of time spent in stopping DDoS attacks (less than 47 seconds) and scalability for scenarios with different number of tenants and UEs (2 virtual tenants deployed in 4 Edge nodes and up to 64 IoT devices or sensors connected to the infrastructure).

Original language	English
Title of host publication	Proceedings of the 2023 IEEE 31st International Conference on Network Protocols (ICNP)
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	9798350303223
ISBN (Print)	9798350303230
DOIs	https://doi.org/10.1109/ICNP59255.2023.10355595
Publication status	Published - 20 Dec 2023
Event	2023 IEEE 31st International Conference on Network Protocols Conference - Reykjavik, Iceland Duration: 10 Oct 2023 → 13 Oct 2023 https://ieeexplore.ieee.org/xpl/conhome/10355566/proceeding

Publication series

Name	IEEE Conference Proceedings
Publisher	IEEE
ISSN (Print)	1092-1648
ISSN (Electronic)	2643-3303

Conference

Conference	2023 IEEE 31st International Conference on Network Protocols Conference
Abbreviated title	ICNP 2023
Country/Territory	Iceland
City	Reykjavik
Period	10/10/23 → 13/10/23
Internet address	https://ieeexplore.ieee.org/xpl/conhome/10355566/proceeding

Keywords

network security
IoT
5G
zero touch network management

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ICNP59255.2023.10355595

2023 08 28 Benlloch-Caballero et al Topology accepted - for PureAccepted author manuscript, 968 KBLicence: CC BY 4.0

Cite this

Benlloch-Caballero, P., Sanchez-Navarro, I., Matencio-Escolar, A., Alcaraz Calero, J. M., & Wang, Q. (2023). Topology-aware cognitive self-protection framework for automated detection and mitigation of security and privacy incidents in 5G-IoT networks. In Proceedings of the 2023 IEEE 31st International Conference on Network Protocols (ICNP) (IEEE Conference Proceedings). IEEE. https://doi.org/10.1109/ICNP59255.2023.10355595

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title = "Topology-aware cognitive self-protection framework for automated detection and mitigation of security and privacy incidents in 5G-IoT networks",

abstract = "Internet of Things (IoT) coupled with 5G networks enable unprecedented levels of scalability and performance in the computing industry. These enhanced performance features allow to offer and deploy a wide range of new use cases and services in scenarios such as Smart Cities, Smart Grid or Industry 5.0 just to mention a few. However, the inherent complexity of such networks is a serious concern in terms of security. Furthermore, the vulnerability and low-power constraints of IoT devices make such networks a targeted vector for cyber criminals. In this contribution, authors present an innovative topology-aware Cognitive Self-protection framework able to detect and mitigate attacks in an autonomous way with no human intervention in the wired segments of 5G-IoT multi-tenant networks. Preliminary tests carried out on a realistic emulated testbed show promising results in terms of time spent in stopping DDoS attacks (less than 47 seconds) and scalability for scenarios with different number of tenants and UEs (2 virtual tenants deployed in 4 Edge nodes and up to 64 IoT devices or sensors connected to the infrastructure).",

keywords = "network security, IoT, 5G, zero touch network management",

author = "Pablo Benlloch-Caballero and Ignacio Sanchez-Navarro and Antonio Matencio-Escolar and {Alcaraz Calero}, {Jose M.} and Qi Wang",

year = "2023",

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doi = "10.1109/ICNP59255.2023.10355595",

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booktitle = "Proceedings of the 2023 IEEE 31st International Conference on Network Protocols (ICNP)",

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note = "2023 IEEE 31st International Conference on Network Protocols Conference, ICNP 2023 ; Conference date: 10-10-2023 Through 13-10-2023",

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Benlloch-Caballero, P , Sanchez-Navarro, I, Matencio-Escolar, A, Alcaraz Calero, JM & Wang, Q 2023, Topology-aware cognitive self-protection framework for automated detection and mitigation of security and privacy incidents in 5G-IoT networks. in Proceedings of the 2023 IEEE 31st International Conference on Network Protocols (ICNP). IEEE Conference Proceedings, IEEE, 2023 IEEE 31st International Conference on Network Protocols Conference, Reykjavik, Iceland, 10/10/23. https://doi.org/10.1109/ICNP59255.2023.10355595

Topology-aware cognitive self-protection framework for automated detection and mitigation of security and privacy incidents in 5G-IoT networks. / Benlloch-Caballero, Pablo ; Sanchez-Navarro, Ignacio; Matencio-Escolar, Antonio et al.
Proceedings of the 2023 IEEE 31st International Conference on Network Protocols (ICNP). IEEE, 2023. (IEEE Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Topology-aware cognitive self-protection framework for automated detection and mitigation of security and privacy incidents in 5G-IoT networks

AU - Benlloch-Caballero, Pablo

AU - Sanchez-Navarro, Ignacio

AU - Matencio-Escolar, Antonio

AU - Alcaraz Calero, Jose M.

AU - Wang, Qi

PY - 2023/12/20

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N2 - Internet of Things (IoT) coupled with 5G networks enable unprecedented levels of scalability and performance in the computing industry. These enhanced performance features allow to offer and deploy a wide range of new use cases and services in scenarios such as Smart Cities, Smart Grid or Industry 5.0 just to mention a few. However, the inherent complexity of such networks is a serious concern in terms of security. Furthermore, the vulnerability and low-power constraints of IoT devices make such networks a targeted vector for cyber criminals. In this contribution, authors present an innovative topology-aware Cognitive Self-protection framework able to detect and mitigate attacks in an autonomous way with no human intervention in the wired segments of 5G-IoT multi-tenant networks. Preliminary tests carried out on a realistic emulated testbed show promising results in terms of time spent in stopping DDoS attacks (less than 47 seconds) and scalability for scenarios with different number of tenants and UEs (2 virtual tenants deployed in 4 Edge nodes and up to 64 IoT devices or sensors connected to the infrastructure).

AB - Internet of Things (IoT) coupled with 5G networks enable unprecedented levels of scalability and performance in the computing industry. These enhanced performance features allow to offer and deploy a wide range of new use cases and services in scenarios such as Smart Cities, Smart Grid or Industry 5.0 just to mention a few. However, the inherent complexity of such networks is a serious concern in terms of security. Furthermore, the vulnerability and low-power constraints of IoT devices make such networks a targeted vector for cyber criminals. In this contribution, authors present an innovative topology-aware Cognitive Self-protection framework able to detect and mitigate attacks in an autonomous way with no human intervention in the wired segments of 5G-IoT multi-tenant networks. Preliminary tests carried out on a realistic emulated testbed show promising results in terms of time spent in stopping DDoS attacks (less than 47 seconds) and scalability for scenarios with different number of tenants and UEs (2 virtual tenants deployed in 4 Edge nodes and up to 64 IoT devices or sensors connected to the infrastructure).

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KW - IoT

KW - 5G

KW - zero touch network management

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DO - 10.1109/ICNP59255.2023.10355595

M3 - Conference contribution

SN - 9798350303230

T3 - IEEE Conference Proceedings

BT - Proceedings of the 2023 IEEE 31st International Conference on Network Protocols (ICNP)

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ER -

Benlloch-Caballero P , Sanchez-Navarro I, Matencio-Escolar A, Alcaraz Calero JM , Wang Q. Topology-aware cognitive self-protection framework for automated detection and mitigation of security and privacy incidents in 5G-IoT networks. In Proceedings of the 2023 IEEE 31st International Conference on Network Protocols (ICNP). IEEE. 2023. (IEEE Conference Proceedings). doi: 10.1109/ICNP59255.2023.10355595

Topology-aware cognitive self-protection framework for automated detection and mitigation of security and privacy incidents in 5G-IoT networks

Abstract

Publication series

Conference

Keywords

UN SDGs

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Cite this