The paper proposes a technique for protecting reconfigurable networks that implements topology rebuilding, which combines immunization and network gaming methods, as a solution for maintaining cyber resilience. Immunization presumes an adaptive set of protective reconfigurations destined to ensure the functioning of a network. It is a protective reconfiguration aimed to preserve/increase the functional quality of the system. Network nodes and edges are adaptively reorganized to counteract an invasion. This is a functional component of cyber resilience. It can be implemented as a global strategy, using knowledge of the whole network structure, or a local strategy that only works with a certain part of a network. A formal description of global and local immune strategies based on hierarchical and peer-to-peer network topologies is presented. A network game is a kind of the well-defined game model in which each situation generates a specific network, and the payoff function is calculated based on the constructed networks. A network game is proposed for analyzing a network topology. This model allows quickly identifying nodes that require disconnection or replacement when a cyber attack occurs, and understanding which network sectors might be affected by an attack. The gaming method keeps the network topology resistant to unnecessary connections. This is a structural component of cyber resilience. The basic network game method has been improved by using the criterion of maximum possible path length to reduce the number of reconfigurations. Network optimization works together with immunization to preserve the structural integrity of the network. In an experimental study, the proposed method demonstrated its effectiveness in maintaining system quality within given functional limits and reducing the cost of system protective restructuring.
Maintaining Cyber Resilience in the Reconfigurable Networks with Immunization and Improved Network Game Methods.
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作者:Kalinin Maxim, Pavlenko Evgeny, Gavva Georgij, Pakhomov Maxim
| 期刊: | Sensors | 影响因子: | 3.500 |
| 时间: | 2024 | 起止号: | 2024 Nov 5; 24(22):7116 |
| doi: | 10.3390/s24227116 | ||
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