scholarly journals An information diffusion model in social networks with carrier compartment and delay

2018 ◽  
Vol 23 (4) ◽  
pp. 568-582 ◽  
Author(s):  
Bo Du ◽  
Haiyan Wang ◽  
Maoxing Liu
Keyword(s):  
Communication Networks ◽  
Information Diffusion ◽  
Matrix Theory ◽  
Equilibrium Points ◽  
Propagation Model ◽  
Malware Propagation ◽  
Information Diffusion Model ◽  
Characteristic Values ◽  
Mobile Wireless Sensor ◽  
Sensitive Parameters

With the wide applications of the communication networks, the topic of information networks security is getting more and more attention from governments and individuals. This paper is devoted to investigating a malware propagation model with carrier compartment and delay to describe the process of malware propagation in mobile wireless sensor networks. Based on matrix theory for characteristic values, the local stability criterion of equilibrium points is established. Applying the linear approximation method of nonlinear systems, we study the existence of Hopf bifurcation at the equilibrium points. At the same time, we identify some sensitive parameters in the process of malware propagation. Finally, numerical simulations are performed to illustrate the theoretical results.

scholarly journals Considering Quarantine in the SIRA Malware Propagation Model

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
José Roberto C. Piqueira ◽  
Cristiane M. Batistela
Keyword(s):  
Data Science ◽  
Network Reliability ◽  
Equilibrium Points ◽  
Propagation Model ◽  
Data Networks ◽  
Preventive Actions ◽  
Malware Propagation ◽  
Existence And Stability ◽  
Block Based ◽  
Numerical Approaches

As the beginning of the 21st century was marked by a strong development in data science and, consequently, in computer networks, models for designing preventive actions against intruding, data stealing, and destruction became mandatory. Following this line, several types of epidemiological models have been developed and improved, considering different operational approaches. The development of the research line using traditional SIR(Susceptible, Infected, Removed) model for data networks started in the 1990s. In 2005, an epidemiological compartmental model containing antidotal nodes, SIRA (Susceptible, Infected, Removed, Antidotal), was introduced to study how the antivirus policies affect the network reliability. The idea here is to study the consequence of quarantine actions in a network by modifying the SIRA model, introducing quarantine nodes generating the SIQRA (Susceptible, Infected, Quarantine, Removed, Antidotal) model. Analytical and numerical approaches result in parameter conditions for the existence and stability of disease-free and endemic equilibrium points for two different cases: saturation and nonsaturation of the quarantine population block. Based on these results, operational actions can be planned to improve the network reliability.

scholarly journals Influence Model of User Behavior Characteristics on Information Dissemination

2016 ◽  
Vol 11 (2) ◽  
pp. 209 ◽  
Author(s):  
Shao Chun Han ◽  
Yun Liu ◽  
Hui Ling Chen ◽  
Zhen Jiang Zhang
Keyword(s):  
Human Behavior ◽  
Information Diffusion ◽  
Statistical Physics ◽  
Information Dissemination ◽  
User Behavior ◽  
Activity Patterns ◽  
Propagation Model ◽  
Propagation Time ◽  
Behavior Characteristics ◽  
The Impact

Quantitative analysis on human behavior, especially mining and modeling temporal and spatial regularities, is a common focus of statistical physics and complexity sciences. The in-depth understanding of human behavior helps in explaining many complex socioeconomic phenomena, and in finding applications in public opinion monitoring, disease control, transportation system design, calling center services, information recommendation. In this paper,we study the impact of human activity patterns on information diffusion. Using SIR propagation model and empirical data, conduct quantitative research on the impact of user behavior on information dissemination. It is found that when the exponent is small, user behavioral characteristics have features of many new dissemination nodes, fast information dissemination, but information continued propagation time is short, with limited influence; when the exponent is big, there are fewer new dissemination nodes, but will expand the scope of information dissemination and extend information dissemination duration; it is also found that for group behaviors, the power-law characteristic a greater impact on the speed of information dissemination than individual behaviors. This study provides a reference to better understand influence of social networking user behavior characteristics on information dissemination and kinetic effect.

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