Disinformation spreading control model based on key nodes bi-objective optimization

被引：0
作者：
Jing J. [1 ,2 ]
Zhang Z. [1 ,2 ]
Ban A. [1 ,2 ]
Gao D. [1 ,2 ]
机构：
[1] Information Engineering College, Henan University of Science and Technology, Luoyang
[2] Henan International Joint Laboratory of Cyberspace Security Applications, Henan University of Science and Technology, Luoyang
来源：
Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University | 2024年 / 51卷 / 01期
关键词：
disinformation; genetic algorithm; key nodes; non-dominated sorting genetic algorithm-Ⅱ; social network;
D O I：
10.19665/j.issn1001-2400.20230209
中图分类号：
学科分类号：
摘要：
The spread control of disinformation is a hot area of global cyberspace security governance.At present,the research on the spread control of disinformation in online social networks has not considered the actual problem of the cost incurred by the control of key nodes set.This paper proposes a disinformation spreading control model based on key nodes bi-objective optimization.First,according to the spread influence of social user nodes in the 1-hop and 2-hop areas,as well as the degree centrality of nodes,k-shell and other complex network characteristics,the bi-objective including the control effect and control cost is expressed mathematically.Second,a bit flipping mutation algorithm incorporating adaptive nonlinear strategy is designed to improve the performance of the NSGA-Ⅱ algorithm in discrete search space.The improved NSGA-Ⅱ algorithm is used to select a key nodes set of disinformation spreading,which maximizes the effect of disinformation spreading control and minimizes the control cost.Finally,the experiment is carried out on a real online social network platform,with the influence of model parameters on the control cost and control effect analyzed and discussed.Experimental results show that this model has specific and obvious advantages over the existing methods in the combination index RTCTE of control cost and control effect.This model is applicable to the lowest cost disinformation spreading control in large-scale complex social networks. © 2024 Science Press. All rights reserved.
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页码：201 / 209
页数：8
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