Network key point analysis method based on single-layer information flow transmission

Abstract

The invention discloses a network key point analysis method based on single-layer information flow transmission, and the method comprises the steps: obtaining network data based on a graph structure,and constructing a single-layer information flow transmission network according to the network data; preprocessing the single-layer information flow transmission network, and establishing an optimization objective function based on a network attacker and a network operator; constructing a game model according to the optimization objective functions of the network attacker and the network operator;establishing a single-layer network information flow blocking model from the perspective of the network attacker, and blocking nodes are determined as network key points. According to the invention,two concepts of a network attacker and a network operator are introduced to describe the problem of network security from different perspectives and construct a game model; and meanwhile, the targetsof the network attacker and the network operator are clearly described and are classified into the same model, so that a single-layer network information flow blocking model is established, and key nodes of the network are discovered while a blocking scheme is solved from the perspective of the attacker.

Description

technical field [0001] The invention relates to the technical field of complex networks, in particular to a network key point analysis method based on single-layer information flow transmission. Background technique [0002] Computer network functions mainly include realizing resource sharing, realizing rapid transmission of data information, improving reliability, providing load balancing and distributed processing capabilities, centralized management and comprehensive information services; the above functions can be abstractly summarized as: information flow transmission, key network nodes Or node clusters for information processing and network performance optimization. [0003] The key nodes of the network refer to some special nodes that can affect the structure or performance of the network to a greater extent than other nodes in the network. The failure of some nodes in the network may cause small-scale failure or load redistribution, which has little impact on the ov...

AI Technical Summary

Problems solved by technology

[0004] So far, a large number of methods for evaluating key nodes of the network have been proposed, such as degree centrality, betweenness centrality, proximity centrality, semi-local centrality, etc., but all have their own limitations.

Among them, 1. Degree centrality is a relatively direct indicator, but usually it is not very important or correct. Similar indicators include LocalRank, proximity and H index, etc.; 2. Betweenness centrality and proximity centrality Both are path-based centrality, which is a global metric and can more effectively identify key nodes in the network, but their computational complexity is higher; 3. Semi-local centrality aims to ignore the topological relationship between neighbors and Con

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