Please wait a minute...
Chin. Phys. B, 2025, Vol. 34(2): 028701    DOI: 10.1088/1674-1056/ad9ff8
INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY Prev   Next  

Triadic percolation in computer virus spreading dynamics

Jie Gao(高杰)1, Jianfeng Luo(罗建锋)1, Xing Li(李星)1, Yihong Li(李毅红)1, Zunguang Guo(郭尊光)2, and Xiaofeng Luo(罗晓峰)1,†
1 School of Mathematics, North University of China, Taiyuan 030051, China;
2 Department of Science, Taiyuan Institute of Technology, Taiyuan 030008, China
Abstract  In recent years, the threats posed by computer viruses have become increasingly diverse and complex. While classic percolation theory provides a novel perspective for analyzing epidemics and information dissemination, it fails to capture the temporal dynamics of these systems and the effects of virus invasion and governmental regulation. Triadic percolation theory, a recent advancement, addresses these limitations. In this paper, we apply this new percolation mechanism to model the diffusion of computer viruses, deriving a precise mathematical formulation of the triadic percolation model and providing an analytical solution of the triadic percolation threshold. Additionally, we investigate the impact of nonlinear transmission probability characteristics on virus propagation. Numerical simulations demonstrate that reducing the network's average degree (or the positive regulation) or increasing regulatory interventions raises the outbreak threshold for computer viruses while decreasing their final size. Moreover, the study reveals that nonlinear transmission probabilities result in an increased number of solutions for the final size of the computer viruses. Our findings contribute new insights into controlling the spread of computer viruses.
Keywords:  triadic percolation      percolation threshold      nonlinear transmission probability      final size  
Received:  15 October 2024      Revised:  04 December 2024      Accepted manuscript online:  17 December 2024
PACS:  87.23.Kg (Dynamics of evolution)  
  05.45.-a (Nonlinear dynamics and chaos)  
  02.60.Cb (Numerical simulation; solution of equations)  
Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 12101573 and 12022113) and the Fundamental Research Program of Shanxi Province, China (Grant Nos. 20210302124381, 202203021211213, and 20210302123018).
Corresponding Authors:  Xiaofeng Luo     E-mail:  luoxiaofeng@nuc.edu.cn

Cite this article: 

Jie Gao(高杰), Jianfeng Luo(罗建锋), Xing Li(李星), Yihong Li(李毅红), Zunguang Guo(郭尊光), and Xiaofeng Luo(罗晓峰) Triadic percolation in computer virus spreading dynamics 2025 Chin. Phys. B 34 028701

[1] Cohen F 1987 Comput. Secur. 6 22
[2] Balthrop J, Forrest S, Newman M E and William son MM2004 Science 304 527
[3] Essam J W 1980 Rep. Prog. Phys. 43 833
[4] Stauffer D and Aharony A 2018 Introduction to percolation theory, 2nd Edn. (London: Taylor & Francis) pp. 1-192
[5] Sun H L and Bianconi G 2021 Phys. Rev. E 104 034306
[6] Li M, Liu R R, Lü L Y, Hu M B, Xu S Q and Zhang Y C 2021 Phys. Rep. 907 1
[7] Zhu J C and Wang L W 2022 Chin. Phys. B 31 068904
[8] Broadbent S R and Hammersley JM1957 Math. Proc. Cambridge Philos. Soc. 53 629
[9] Moore C and Newman M E 2000 Phys. Rev. E 62 7059
[10] Meyers L 2007 Bull. Am. Math. Soc. 44 63
[11] Newman M E 2002 Phys. Rev. E 66 016128
[12] Cardy J L and Grassberger P 1985 J. Phys. A Math. Gen. 18 267
[13] Chang L L, Gong W, Jin Z and Sun G Q 2022 Siam J. Appl. Math. 82 1764
[14] Sun G Q, He R Z, Hou L F, Gao S P, Luo X F, Liu Q H, Zhang Y C and Chang L L 2024 Europhys. Lett. 147 12001
[15] Xie J R, Meng F H, Sun J C, Ma X, Yan G and Hu Y Q 2021 Nat. Hum. Behav. 5 1161
[16] Palmieri F 2012 J. Syst. Softw. 85 2559
[17] Liu Y, Wei B, Wang Z and Deng Y 2015 Phys. Lett. A 379 2795
[18] Mann P, Smith V A, Mitchell J B and Dobson S 2021 Phys. Rev. E 104 024303
[19] Shang Y 2021 Chaos 31 053117
[20] Liu S M, Bai Z G and Sun G Q 2023 Nonlinearity 36 5699
[21] Luo X F and Jin Z 2020 Commun. Nonlinear Sci. Numer. Simul. 91 105363
[22] Sun H L, Radicchi F, Kurths J and Bianconi G 2023 Nat. Commun. 14 1308
[23] Millán A P, Sun H, Torres J J and Bianconi G 2024 Pans Nexus 3 270
[24] Raza A, Arif M S, Rafiq M, Bibi M, Naveed M, Iqbal M U, Butt Z, Naseem H A and Abbasi J N 2019 Cmes-Comp. Model Eng. 120 445
[25] Dubey V P, Kumar R and Kumar D 2020 Chaos, Solitons and Fractals 133 109626
[26] Zarin R, Khaliq H, Khan A, Ahmed I and Humphries UW2023 Csymmetry 15 621
[27] Han X and Tan Q L 2010 Appl. Math. Comput. 217 2520
[28] Murray W H 1988 Icomput. Secur. 7 139
[29] He R Z, Luo X F, Asamoah J K K, Zhang Y X, Li Y H, Jin Z and Sun G Q 2023 J. Math. Biol. 87 29
[30] Luo X F, Sun G Q, He R Z, Jin Z, Asamoah J K K, Xue Y K and Chang L L 2024 Chaos 34 073114
[31] Mishra B K and Saini D 2007 Appl. Math. Comput. 187 929
[32] Zhu Q Y, Yang X F and Ren J G 2012 Commun. Nonlinear Sci. Numer. Simul. 17 5117
[33] Ren J G, Yang X F, Zhu Q Y, Yang L X and Zhang CM2012 Nonlinear Anal-Real 3 376
[34] Zarin R, Khaliq H, Khan A, Khan D, Akgül A and Humphries U W 2022 Results Phys. 33 105130
[35] Singh J, Kumar D, Hammouch Z and Atangana A 2018 Appl. Math. Comput. 316 504
[36] Gan C Q, Feng Q D, Zhu Q Y, Zhang Z F, Zhang Y S and Xiang Y 2020 Nonlinear Dyn. 100 1725
[37] Lefebvre M 2020 Atti della Accademia Peloritana dei Pericolanti-Classe di Scienze Fisiche, Matematiche e Naturali 98 3
[38] Yang F F and Zhang Z Z 2021 AIMS Math. 6 4083
[39] Gao Y L, Yu H B, Zhou J, Zhou Y Z and Chen S M 2023 Chin. Phys. B 32 098902
[40] Avcı D and Soytürk F 2023 J. Comput. Appl. Math. 419 114740
[41] Yang L X and Yang X F 2015 Nonlinear Dyn. 82 85
[42] Gan C Q, Yang X F, Liu W P, Zhu Q Y and Zhang X L 2013 Appl. Math. Comput. 4222 265
[43] d’Onofrio A, Manfredi P and Salinelli E 2007 Theor. Popul Biol. 71 301
[44] Newman M 2018 Networks, 2nd Edn. (Oxford University Press) pp. 569-602
[45] Kondakci S 2008 Simul. Modell. Pract. Theory 16 571
[1] A Weibo local network growth model constructed from the perspective of following-followed
Fu-Zhong Nian(年福忠) and Ran-Qing Yao(姚然庆). Chin. Phys. B, 2024, 33(12): 128702.
[2] Prediction of ILI following the COVID-19 pandemic in China by using a partial differential equation
Xu Zhang(张栩), Yu-Rong Song(宋玉蓉), and Ru-Qi Li(李汝琦). Chin. Phys. B, 2024, 33(11): 110201.
[3] Effects of individual heterogeneity on social contagions
Fu-Zhong Nian(年福忠) and Yu Yang(杨宇). Chin. Phys. B, 2024, 33(5): 058705.
[4] Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels
Xiao-Xiao Xie(谢笑笑), Liang-An Huo(霍良安), Ya-Fang Dong(董雅芳), and Ying-Ying Cheng(程英英). Chin. Phys. B, 2024, 33(3): 038704.
[5] Studying the co-evolution of information diffusion, vaccination behavior and disease transmission in multilayer networks with local and global effects
Liang'an Huo(霍良安) and Bingjie Wu(武兵杰). Chin. Phys. B, 2024, 33(3): 038702.
[6] Impact of individual behavior adoption heterogeneity on epidemic transmission in multiplex networks
Liang'an Huo(霍良安) and Yue Yu(于跃). Chin. Phys. B, 2023, 32(10): 108703.
[7] Fitness of others' evaluation effect promotes cooperation in spatial public goods game
Jian-Wei Wang(王建伟), Rong Wang(王蓉), and Feng-Yuan Yu(于逢源). Chin. Phys. B, 2021, 30(12): 128701.
[8] Continuous non-autonomous memristive Rulkov model with extreme multistability
Quan Xu(徐权), Tong Liu(刘通), Cheng-Tao Feng(冯成涛), Han Bao(包涵), Hua-Gan Wu(武花干), and Bo-Cheng Bao(包伯成). Chin. Phys. B, 2021, 30(12): 128702.
[9] Reputational preference and other-regarding preference based rewarding mechanism promotes cooperation in spatial social dilemmas
Huayan Pei(裴华艳), Guanghui Yan(闫光辉), and Huanmin Wang(王焕民). Chin. Phys. B, 2021, 30(5): 050203.
[10] Benefit community promotes evolution of cooperation in prisoners' dilemma game
Jianwei Wang(王建伟), Jialu He(何佳陆), Fengyuan Yu(于逢源), Wei Chen(陈伟), Rong Wang(王蓉), Ke Yu(于可). Chin. Phys. B, 2019, 28(10): 108703.
[11] The most common friend first immunization
Fu-Zhong Nian(年福忠), Cha-Sheng Hu(胡茶升). Chin. Phys. B, 2016, 25(12): 128702.
[12] Spatial snowdrift game in heterogeneous agent systems with co-evolutionary strategies and updating rules
Xia Hai-Jiang (夏海江), Li Ping-Ping (李萍萍), Ke Jian-Hong (柯见洪), Lin Zhen-Quan (林振权). Chin. Phys. B, 2015, 24(4): 040203.
[13] Near equilibrium dynamics and one-dimensional spatial-temporal structures of polar active liquid crystals
Yang Xiao-Gang (杨小刚), M. Gregory Forest, Wang Qi (王奇). Chin. Phys. B, 2014, 23(11): 118701.
[14] Integrating the environmental factor into the strategy updating rule to promote cooperation in evolutionary games
Zhao Lin(赵琳), Zhou Xin(周鑫), Liang Zhi(梁治), and Wu Jia-Rui(吴家睿) . Chin. Phys. B, 2012, 21(1): 018701.
[15] Evolutionary games in a generalized Moran process with arbitrary selection strength and mutation
Quan Ji(全吉) and Wang Xian-Jia(王先甲) . Chin. Phys. B, 2011, 20(3): 030203.
No Suggested Reading articles found!