Extending Defense-in-Depth to Multi-Domain Networks

Multi-domain networks, consisting of interconnected management domains with distinct control mechanisms, introduce unique cybersecurity challenges that are often overlooked in current research. This paper addresses these gaps by providing a formal definition of multi-domain networks and their management domains, emphasizing the security implications of inter-domain relationships. We extend the traditional Defense-in-Depth (DiD) strategy to account for both intra-domain security and cross-domain interactions, presenting a novel framework for DiD in multi-domain environments. A tri-objective optimization problem is formulated to balance defense effectiveness, resource costs, and operational impacts, which is solved using an improved genetic algorithm (IGADS). Simulations demonstrate the efficacy of this approach, offering a robust defense schema for securing multi-domain networks.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1145/3711129.3711254
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
0.00
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article

Extending Defense-in-Depth to Multi-Domain Networks

J. Z. Zhang, Junhai Yang, Ziyan Zhou, Yaobing Xu et al.
Software-Defined Networks and 5G
article

Extending Defense-in-Depth to Multi-Domain Networks

J. Z. Zhang, Junhai Yang, Ziyan Zhou, Yaobing Xu, Xuhua Shi, Jing Wang
article en

Abstract

Multi-domain networks, consisting of interconnected management domains with distinct control mechanisms, introduce unique cybersecurity challenges that are often overlooked in current research. This paper addresses these gaps by providing a formal definition of multi-domain networks and their management domains, emphasizing the security implications of inter-domain relationships. We extend the traditional Defense-in-Depth (DiD) strategy to account for both intra-domain security and cross-domain interactions, presenting a novel framework for DiD in multi-domain environments. A tri-objective optimization problem is formulated to balance defense effectiveness, resource costs, and operational impacts, which is solved using an improved genetic algorithm (IGADS). Simulations demonstrate the efficacy of this approach, offering a robust defense schema for securing multi-domain networks.

Chinese Academy of Sciences (CN), Institute of Information Engineering (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 68%
Software-Defined Networks and 5G
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