关键节点双目标优化的虚假信息传播控制模型

doi:10.19665/j.issn1001-2400.20230209

摘要/Abstract

摘要：

虚假信息传播控制是全球网络空间安全治理的热点领域。针对目前在线社交网络中的虚假信息传播控制研究,尚未考虑对关键节点集控制所产生的成本开销这一实际问题,提出了一种基于关键节点双目标优化的虚假信息传播控制模型。首先,根据用户节点在社交网络1-hop和2-hop区域的传播影响力以及节点的度中心性、k-shell等多种复杂网络特征,对两个优化目标(控制效果和控制成本)进行数学形式化表示;其次,设计一种融合自适应非线性策略的位翻转变异算法,实现对离散搜索空间的第2代非支配排序遗传算法改进,并将改进后第2代非支配排序遗传算法用于虚假信息传播关键节点集的选取,从而实现虚假信息传播控制效果最大化,控制成本开销最小化;最后,通过在真实在线社交网络平台上开展实验,分析模型参数对控制成本和控制效果的影响。实验结果表明,该模型与现有方法相比,在控制成本和控制效果的组合指标R_TCTE上具有明显的优势。该模型适用于大规模复杂社交网络下最低成本的虚假信息传播控制。

关键词: 社交网络, 虚假信息, 关键节点, 遗传算法, 第2代非支配排序遗传算法

Abstract:

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 R_TCTE of control cost and control effect.This model is applicable to the lowest cost disinformation spreading control in large-scale complex social networks.

Key words: social network, disinformation, key nodes, genetic algorithm, non-dominated sorting genetic algorithm-Ⅱ

中图分类号:

TP309

荆军昌, 张志勇, 班爱莹. 关键节点双目标优化的虚假信息传播控制模型[J]. 西安电子科技大学学报, 2024, 51(1): 201-209.

JING Junchang, ZHANG Zhiyong, BAN Aiying. Disinformation spreading control model based on key nodes bi-objective optimization[J]. Journal of Xidian University, 2024, 51(1): 201-209.

图/表 5

参考文献 22

[1]	BUTCHER P. COVID-19 as a Turning Point in the Fight Against Disinformation[J]. Nature Electronics, 2021, 4(1):7-9. doi: 10.1038/s41928-020-00532-2
[2]	CHOI D J, OH H, CHUN S, et al. Preventing Rumor Spread with Deep Learning[J]. Expert Systems with Applications, 2022, 197:116688. doi: 10.1016/j.eswa.2022.116688
[3]	张志勇, 荆军昌, 李斐, 等. 人工智能视角下的在线社交网络虚假信息检测、传播与控制研究综述[J]. 计算机学报, 2021, 44(11):2261-2282.
	ZHANG Zhiyong, JING Junchang, LI Fei, et al. Survey on Fake Information Detection,Propagation and Control in Online Social Networks from the Perspective of Artificial Intelligence[J]. Chinese Journal of Computer, 2021, 44(11):2261-2282.
[4]	BONDIELLI A, MARCELLONI F. A Survey on Fake News andRumour Detection Techniques[J]. Information Sciences, 2019, 497:38-55. doi: 10.1016/j.ins.2019.05.035
[5]	DONG X, VICTOR U, QIAN L. Two-Path Deep Semi-Supervised Learning for Timely Fake News Detection[J]. IEEE Transactions on Computational Social Systems, 2020, 7(6):1386-1398. doi: 10.1109/TCSS.6570650
[6]	GOLDANI M H, MOMTAZI S, SAFABAKHSH R. Detecting Fake News with Capsule Neural Networks[J]. Applied Soft Computing, 2021, 101(1):106991. doi: 10.1016/j.asoc.2020.106991
[7]	JIA J F, LIU X W, ZHANG Y X, et al. Rumor Propagation Controlling Based on Finding Important Nodes in Complex Network[J]. Journal of Industrial and Management Optimization, 2020, 16(5):2521-2529. doi: 10.3934/jimo.2019067
[8]	CHEN W N, TAN D Z, YANG Q, et al. Ant Colony Optimization for the Control of Pollutant Spreading on Social Networks[J]. IEEE Transactions on Cybernetics, 2020, 50(9):4053-4065. doi: 10.1109/TCYB.6221036
[9]	TANG J X, ZHANG R S, YAO Y B, et al. Identification of Top-k Influential Nodes Based on Enhanced Discrete Particle Swarm Optimization for Influence Maximization[J]. Physica A:Statistical Mechanics and Its Applications, 2018, 513:477-496. doi: 10.1016/j.physa.2018.09.040
[10]	LIU Z L, QIN T, SUN Q D, et al. SIRQU:Dynamic Quarantine Defense Model for Online Rumor Propagation Control[J]. IEEE Transactions on Computational Social Systems, 2022, 9(6):1703-1714. doi: 10.1109/TCSS.2022.3161252
[11]	PARIMI P, ROUT R R. Genetic Algorithm Based Rumor Mitigation in Online Social Networks Through Counter-Rumors:A Multi-Objective Optimization[J]. Information Processing & Management, 2021, 58(5):102669. doi: 10.1016/j.ipm.2021.102669
[12]	樊田田, 许蕾, 陈林. 基于多目标优化算法NSGA-II推荐相似缺陷报告[J]. 计算机学报, 2019, 42(10):2175-2189.
	FAN Tiantian, XU Lei, CHEN Lin. Recommending Similar Bug Reports Based on Multi-Targets Optimization Algorithm NSGA-II[J]. Chinese Journal of Computer, 2019, 42(10):2175-2189.
[13]	ISMAIL M A, KARAM M S, NOUR M, et al. An Automated Task Scheduling Model Using Non-Dominated Sorting Genetic Algorithm II for Fog-Cloud Systems[J]. IEEE Transactions on Cloud Computing, 2020, 10(4):2294-2308. doi: 10.1109/TCC.2020.3032386
[14]	杜文占, 余志勇, 杨剑, 等. 改进NSGA-II算法及监测天线部署优化研究[J]. 西安电子科技大学学报, 2021, 48(5):239-248.
	DU Wenzhan, YU Zhiyong, YANG Jian, et al. Improved NSGA-II Algorithm and Research on Monitoring Antenna Optimization Deployment[J]. Journal of Xidian University, 2021, 48(5):239-248.
[15]	GONG M G, YAN J N, SHEN B, et al. Influence Maximization in Social Networks Based on Discrete Particle Swarm Optimization[J]. Information Sciences, 2016, 367:600-614.
[16]	LI Z, WANG X. Identifying Influential Spreaders in Complex Networks by an Improved Gravity Model[J]. Scientific Reports, 2021, 11(1):22194. doi: 10.1038/s41598-021-01218-1 pmid: 34772970
[17]	DEB K, PRATAP A, AGARWAL S, et al. A Fast and Elitist Multiobjective Genetic Algorithm:NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2):182-197. doi: 10.1109/4235.996017
[18]	MILLER B L, GOLDBERG D E. Genetic Algorithms,Tournament Selection,and the Effects of Noise[J]. Complex Systems, 1995, 9(3):193-212.
[19]	ZHANG Z Y, SUN RR, ZHAO C W, et al. CyVOD:A Novel Trinity Multimedia Social Network Scheme[J]. Multimedia Tools and Applications, 2017, 76(18):18513-18529. doi: 10.1007/s11042-016-4162-z
[20]	JING J C, ZHANG Z Y, CHOO KK R, et al. Inference of User Desires to Spread Disinformation Based on Social Situation Analytics and Group Effect[J]. IEEE Transactions on Dependable and Secure Computing, 2023, 20(3):1833-1848. doi: 10.1109/TDSC.2022.3165324
[21]	JING J C, LI F, SONG B, et al. Disinformation Propagation Trend Analysis and Identification Based on Social Situation Analytics and Multilevel Attention Network[J]. IEEE Transactions on Computational Social Systems, 2023, 10(2):507-522. doi: 10.1109/TCSS.2022.3169132
[22]	ZHANG Z Y, SUN RR, WANG X X, et al. A Situational Analytic Method for User Behavior Pattern in Multimedia Social Networks[J]. IEEE Transactions on Big Data, 2019, 5(4):520-528. doi: 10.1109/TBigData.6687317

参数名称	取值范围
P_s	20	40	60	80	100
P_c	0.2	0.4	0.6	0.8	1.0
P_m	0.01	0.05	0.10	0.15	0.20