Computer Science ›› 2021, Vol. 48 ›› Issue (3): 313-319.doi: 10.11896/jsjkx.200400079

• Information Security • Previous Articles     Next Articles

Intervention Algorithm for Distorted Information in Online Social Networks Based on Stackelberg Game

YUAN De-yu1,2, CHEN Shi-cong1, GAO Jian1,2, WANG Xiao-juan3   

  1. 1 Department of Police Information Engineering and Cyber Security,People’s Public Security University of China,Beijing 100038,China
    2 Key Laboratory of Safety Precautions and Risk Assessment,Ministry of Public Security,Beijing 100038,China
    3 School of Electronic and Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China
  • Received:2020-04-20 Revised:2020-07-29 Online:2021-03-15 Published:2021-03-05
  • About author:YUAN De-yu,born in 1986,Ph.D,lecturer,Ph.D supervisor.His main research interests include cyber security and complex networks.
    GAO Jian,born in 1982,Ph.D,associate professor.His main research interests include cyber security,malware and botnet.
  • Supported by:
    National Natural Science Foundation of China(61771072),Special Project of People’s Public Security University of China(2020JWCX01) and Open Project of the Key Laboratory of the Police Internet of Things Application Technology (Ministry of Public Security).

Abstract: During the 2019-nCoV epidemic,social media spread news around the world at an unprecedented rate.Distorted information is hidden in massive social data,which presents unprecedented challenges to national security and social stability.Most of the current intervention strategies are based on the control of key nodes and key links,that is,deleting tweets and blocking accounts,which are often ineffective and prone to side effects.Based on the definition and analysis of distorted information,this paper breaks the limitation of traditional thinking and disturbs the evolution of distorted information by publishing clarifications during the spread of distorted information.With the help of Stackelberg game theory,more users are encouraged to participate in the information hedging process by setting up rewards,thereby hindering the explosive effect of distorted information.Based on the established Stackelberg game,the existence and uniqueness of the equilibrium solution are analyzed,and the closed equilibrium solution and information intervention algorithm is proposed.Simulation experiments in the actual network show that the proposed algorithm reduces the spread of distorted information by up to 41% and 9% compared to the traditional immune strategy based on network structure and other intervention algorithms based on game theory,thus can effectively suppress the spread of distor-ted information.

Key words: Distorted information, Information dissemination, Online social networks, Reverse intervention, Stackelberg game

CLC Number: 

  • TP309
[1]WANG J K,YU H,WANG X H,et al.Dissemination and control model of public opinion in online social networks based on users’ relative weight[J].Systems Engineering-Theory & Practice,2019,39(6):1565-1579.
[2]ZUO L M,XIA P P,HU K X,et al.Propagation model of public opinion about ICO in social network environment[J].Computer Engineering and Design,2019,40(11):3247-3253.
[3]PENG S,WANG G,ZHOU Y,et al.An Immunization Framework for Social Networks Through Big Data Based Influence Modeling[J].IEEE Transactions on Dependable and Secure Computing,2019,16(6):984-995.
[4]SHANG R H,ZHANG W T,JIAO L C,et al.Dynamic Immunization Node Model for Complex Networks Based on Community Structure and Threshold[J].IEEE Transactions on Cyberne-tics,2020(5):1-14.
[5]XIN Y,GAO C,WANG Z,et al.Discerning influential spreaders in complex networks by accounting the spreading heterogeneity of the nodes[J].IEEE Access,2019,7:92070-92078.
[6]LIU Y,WANG X,KURTHS J.Framework of Evolutionary Algorithm for Investigation of Influential Nodes in Complex Networks[J].IEEE Transactions on Evolutionary Computation,2019,23(6):1049-1063.
[7]YANG Y,WU C X,HE M,et al.Negative Influence Minimization Algorithm for Social Networks[J/OL].Journal of System Simulation.
[8]ZHUKOV D,ZALTCMAN A G,KHVATOVA T Y.Forecasting Changes in States in Social Networks and Sentiment Security Using the Principles of Percolation Theory and Stochastic Dynamics[C]//2019 International Conference on Quality Management,Transport and Information Security,Information Technologies(IT&QM&IS).2019:149-153.
[9]ZHENG J,PAN L.Least Cost Rumor Community Blocking optimization in Social Networks[C]//Third International Confe-rence on Security of Smart Cities,Industrial Control System and Communications (SSIC).2018.
[10]JOHNSON N F,LEAHY R,RESTREPO N J,et al.Hidden resilience and adaptive dynamics of the global online hate ecology[J].Nature,2019,573:261-265.
[11]XIAO Y P,YANG Q F,SANG C Y,et al.Rumor DiffusionModel Based on Representation Learning and Anti-Rumor[J].IEEE Transactions on Network and Service Management,2020(5):1-14.
[12]TONG G M,WU W L,GUO L,et al.An Efficient Randomized Algorithm for Rumor Blocking in Online Social Networks[J].arXiv:1701.02368.
[13]SRIVASTAVA A,KANNAN R,CHELMIS C,et al.RecANt:Network-based Recruitment for Active Fake News Correction[C]//2019 IEEE International Conference on Big Data (Big Data).2019:940-949.
[14]YU Y X,WANG L.An advertising game theory decision-ma-king mechanism for overlapping seeds in geo-social network[J].Journal of Computer Research and Development,2019,56(6):1302-1311.
[15]SHAN F F,LI H,ZHU H.Game theory based forwarding control method for social network[J].Journal on Communications,2018,39(3):172-180.
[16]YAO C,ZHANG Y,ZHANG X,et al.Competitive InfluenceBlocking in Online Social Networks:A Case Study on WeChat
[C]//2018 24th Asia-Pacific Conference on Communications (APCC).2018:251-256.
[17]LU P E,PENG Y H,CHANG C S,et al.Percolation Threshold for Competitive Influence in Random Networks[J/OL].IEEE Transactions on Computational Social Systems. 1904.05754.pdf,2020.
[18]LIU Y Z,PAN X Z,FU W.Social Network Rumor Spreading Model Based on Bandwagon Game Between Nodes[J].Compu-ter Engineering,2018,44(10):309-314.
[19]LI Q,WANG Z,WU B,et al.Competition and Cooperation:Dynamical Interplay Diffusion Between Social Topic Multiple Messages in Multiplex Networks[J].IEEE Transactions on Computational Social Systems,2019,6(3):467-478.
[20]KALIGOTLA C,YÜCESAN E,CHICK S E.An agent based model of spread of competing rumors through online interactions on social media[C]//Proceedings of the 2015 Winter Simulation Conference.2015:3985-3996.
[21]HE Z,CAI Z,YU J,et al.Cost-efficient strategies for restraining rumor spreading in mobile social networks[J].IEEE Trans.Veh.Technol.,2017,66(3):2789-2800.
[22]MYERSON R B.Game theory:analysis of conflict[M].Harvard University Press,1997.
[23]WAN P,WANG X,WANG X,et al.Intervening coupling diffusion of competitive information in online social networks[J].IEEE Transactions on Knowledge and Data Engineering.DOI:10.1109/TKDE.2019.2954901.
[1] CHANG Ya-wen, YANG Bo, GAO Yue-lin, HUANG Jing-yun. Modeling and Analysis of WeChat Official Account Information Dissemination Based on SEIR [J]. Computer Science, 2022, 49(4): 56-66.
[2] ZHANG Jie, YUE Shao-hua, WANG Gang, LIU Jia-yi, YAO Xiao-qiang. Multi-agent System Based on Stackelberg and Edge Laplace Matrix [J]. Computer Science, 2021, 48(8): 253-262.
[3] SANG Chun-yan, XU Wen, JIA Chao-long, WEN Jun-hao. Prediction of Evolution Trend of Online Public Opinion Events Based on Attention Mechanism in Social Networks [J]. Computer Science, 2021, 48(7): 118-123.
[4] BAO Jun-bo, YAN Guang-hui, LI Jun-cheng. SIR Propagation Model Combing Incomplete Information Game [J]. Computer Science, 2020, 47(6): 230-235.
[5] YUAN De-yu, GAO Jian, YE Meng-xi, WANG Xiao-juan,. Malicious Information Source Locating Algorithm Based on Topological Extension in Online Social Network [J]. Computer Science, 2019, 46(5): 129-134.
[6] LI Fang-wei, ZHOU Jia-wei, ZHANG Hai-bo. Anti-eavesdropping Physical Layer Transmission Scheme Based on Time-reversal in D2D Communication Link [J]. Computer Science, 2019, 46(5): 100-104.
[7] FENG Lei, JI Jun-zhong, WU Chen-sheng. New Method for Ranking Scientific Publications with Creditworthiness Mechanism [J]. Computer Science, 2018, 45(11A): 132-137.
[8] ZHANG Lin-zi, JIA Chuan-liang. Study of Propagation Mechanism in Networks Based on Topological Path [J]. Computer Science, 2018, 45(11A): 308-314.
[9] GONG Xu-fu, WEI Cheng-jian, QIAN Zhen, CHE Bao-zhen and SHEN Hang. Maritime Security Research Based on Stackelberg Game [J]. Computer Science, 2017, 44(5): 153-159.
[10] WU Hai-tao and YING Shi. Classifying Interests of Social Media Users Based on Information Content and Social Graph [J]. Computer Science, 2015, 42(4): 185-189.
[11] ZHANG Chi, ZENG Bi-qing, YANG Jin-song and XIE Xiao-hong. Power Control-oriented Spectrum Pricing and Allocation in OFDMA Cognitive Radio Networks [J]. Computer Science, 2015, 42(3): 85-90.
[12] LI Li-yao, SUN Lu-jing and YANG Jia-hai. Research on Online Social Network [J]. Computer Science, 2015, 42(11): 8-21.
[13] ZHANG Yue-yang and LIU Wei. Link Prediction in Uncertain Protein-Protein Interaction Network [J]. Computer Science, 2014, 41(Z11): 399-402.
[14] DU Jun-zhao , LIU Hui , LI Xiao-jun , ZHANG Ying-jun , ZHANG Yun-yang. Performance Evaluation of Information Dissemination Protocol in WSNs Based on RS Erasure Codes [J]. Computer Science, 2011, 38(Z10): 315-318.
[15] ZHENG Qian-bing,ZHU Pei-dong,WANG Yong-wen,XU Ming. Research on Network Protocol Enhancing Mechanisms Based on Online Social Networks [J]. Computer Science, 2011, 38(6): 81-83.
Full text



No Suggested Reading articles found!