A DISCRETE MATHEMATICAL MODEL TO SIMULATE MALWARE SPREADING

2012 ◽  
Vol 23 (10) ◽  
pp. 1250064 ◽  
Author(s):  
A. MARTIN DEL REY ◽  
G. RODRIGUEZ SÁNCHEZ

With the advent and worldwide development of Internet, the study and control of malware spreading has become very important. In this sense, some mathematical models to simulate malware propagation have been proposed in the scientific literature, and usually they are based on differential equations exploiting the similarities with mathematical epidemiology. The great majority of these models study the behavior of a particular type of malware called computer worms; indeed, to the best of our knowledge, no model has been proposed to simulate the spreading of a computer virus (the traditional type of malware which differs from computer worms in several aspects). In this sense, the purpose of this work is to introduce a new mathematical model not based on continuous mathematics tools but on discrete ones, to analyze and study the epidemic behavior of computer virus. Specifically, cellular automata are used in order to design such model.

2009 ◽  
Vol 30 (4) ◽  
pp. 455-462
Author(s):  
Gai-ping Zhao ◽  
Er-yun Chen ◽  
Jie Wu ◽  
Shi-xiong Xu ◽  
M. W. Collins ◽  
...  

Author(s):  
Sudhakar Yadav ◽  
Vivek Kumar

This study develops a mathematical model for describing the dynamics of the banana-nematodes and its pest detection method to help banana farmers. Two criteria: the mathematical model and the type of nematodes pest control system are discussed. The sensitivity analysis, local stability, global stability, and the dynamic behavior of the mathematical model are performed. Further, we also develop and discuss the optimal control mathematical model. This mathematical model represents various modes of management, including the initial release of infected predators as well as the destroying of nematodes. The theoretical results are shown and verified by numerical simulations.


2014 ◽  
Vol 611 ◽  
pp. 325-331
Author(s):  
Ľubica Miková ◽  
Michal Kelemen ◽  
Vladislav Maxim ◽  
Jaromír Jezný

In current practice the use of mathematical models is substantially widespread, reason being the recent increase in development of programs for this purpose, with the option of model simulation in a virtual environment, proportional to the evolving computer technology. The article contains a mathematical model created using Matlab program. The simulation results are compared with scientific literature that addresses DC motors and evaluated. For simplicity, a graphical interface was created.


2012 ◽  
Vol 452-453 ◽  
pp. 607-612
Author(s):  
Fei Huang ◽  
Jia He Cao

The institutional investor selling a large block of shares in the market usually faces with liquidity risk declining the stock’s prices. In the paper, supposing that temporary impact is stochastic and nonlinear function of trading velocity, we establishes the discrete mathematical model and uses PSO to obtain the optimal liquidation strategies of risk aversion, which is a strict concave function. When analyzing the sensitivity of the parameters, we find that the curve becomes higher and steeper with the increase of the parameters or the decrease of , .As the parameter is tremendous, the curve is close to a horizon line.


2021 ◽  
Author(s):  
David A Kennedy

Why would a pathogen evolve to kill its hosts when killing a host ends a pathogen's own opportunity for transmission? A vast body of scientific literature has attempted to answer this question using "trade-off theory," which posits that host mortality persists due to its cost being balanced by benefits of other traits that correlate with host mortality. The most commonly invoked trade-off is the mortality-transmission trade-off, where increasingly harmful pathogens are assumed to transmit at higher rates from hosts while the hosts are alive, but the pathogens truncate their infectious period by killing their hosts. Here I show that costs of mortality are too small to plausibly constrain the evolution of disease severity except in systems where survival is rare. I alternatively propose that disease severity can be much more readily constrained by a cost of behavioral change due to the detection of infection, whereby increasingly harmful pathogens have increasing likelihood of detection and behavioral change following detection, thereby limiting opportunities for transmission. Using a mathematical model, I show the conditions under which detection can limit disease severity. Ultimately, this argument may explain why empirical support for trade-off theory has been limited and mixed.


2018 ◽  
Vol 77 (12) ◽  
pp. 2761-2771
Author(s):  
Guoqiang Zheng ◽  
Kuizu Su ◽  
Shuai Zhang ◽  
Yulan Wang ◽  
Weihong Wang

Abstract Aerobic granular sludge is a kind of microbial polymer formed by self-immobilization under aerobic conditions. It has been widely studied because of its promising application in wastewater treatment. However, the granulation process of aerobic sludge is still a key factor affecting its practical application. In this paper, a three-dimensional (3D) multi-species mathematical model of aerobic granular sludge was constructed using the cellular automata (CA) theory. The growth process of aerobic granular sludge and its spatial distribution of microorganisms were studied under different conditions. The simulation results show that the aerobic granules were smaller under high shear stress and that the autotrophic bacterial content of the granular sludge interior was higher. However, the higher the dissolved oxygen concentration, the larger the size of granular sludge and the higher the content of autotrophic bacteria in the interior of the granular sludge. In addition, inhibition of toxic substances made the aerobic granule size increase more slowly, and the spatial distribution of the autotrophic bacteria and the toxic-substance-degrading bacteria were mainly located in the outer layer, with the heterotrophic bacteria mainly existing in the interior of the granular sludge.


2021 ◽  
Author(s):  
Ivan Yu. Spitsyn ◽  
Aleksandr M. Sinitca ◽  
Vjacheslav V. Gulvanskii ◽  
Dmitrij A. Perevertailo ◽  
Aleksej V. Volkov

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