Abstract
Identifying critical nodes helps people to protect these nodes from attacks and prevent these critical nodes from rapidly infecting other nodes in the network with viruses. Gateway Local Rank (GLR) algorithm cannot distinguish the difference between the importance of nodes near the geometric center of the network and ignores the critical nodes located at the edge of the network, because it only considers the distance between the node and communities. Gateway Local Rank Extension (GLREX) was proposed to improve GLR by adopting the node interplay model, which not only considers the distance between nodes but also the degree of nodes. The node interplay model supposes the interaction force between nodes is inversely proportional to the exponential power of the distance but not the square of the distance. The influence of nodes cannot be spread out uniformly in a circular manner to affect surrounding nodes, so it is different from the gravitational force between objects in the real world, which obeys the inverse-square law. Because of the node interplay model, GLREX not only considers the interplay between nodes and communities but also the interplay between communities and communities. The experiments showed that compared to GLR, GLREX can effectively identify the critical nodes at different positions of the network.
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The research in this paper was supported by the 13th Five-Year Plan Foundation of Equipment Development Department Founding No. (41401020401, 41401010201).
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Zhang, L., Yan, X. (2021). A Critical Node Detection Algorithm Based Node Interplay Model. In: Wang, G., Chen, B., Li, W., Di Pietro, R., Yan, X., Han, H. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2020. Lecture Notes in Computer Science(), vol 12383. Springer, Cham. https://doi.org/10.1007/978-3-030-68884-4_39
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