Mathematical modeling of the propagation of malware: a review

Rey, Ángel Martín del

doi:10.1002/sec.1186

Cited by 79 publications

(24 citation statements)

References 75 publications

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“…If l iq = 0, the process will remain forever in s 0 , however, if l iq .0, the probability will be l iq Dt + o(Dt), denoting the probability of a change in the state during Dt. It follows from equation (17) that Pfy.tg is some function of t. If, assume, u(s) = Pfy.sg, then the process will be in the same state at time t 0 + s as at time t 0 , and hence its subsequent behavior will be similar to that of s = 0. Especially,…”

Section: Infection To Quarantinementioning

confidence: 99%

Building epidemic models for living populations and computer networks

Kondakci¹,

Kondakci²

2021

Science Progress

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Accurate modeling of viral outbreaks in living populations and computer networks is a prominent research field. Many researchers are in search for simple and realistic models to manage preventive resources and implement effective measures against hazardous circumstances. The ongoing Covid-19 pandemic has revealed the fact about deficiencies in health resource planning of some countries having relatively high case count and death toll. A unique epidemic model incorporating stochastic processes and queuing theory is presented, which was evaluated by computer simulation using pre-processed data obtained from an urban clinic providing family health services. Covid-19 data from a local corona-center was used as the initial model parameters (e.g. [Formula: see text], infection rate, local population size, number of contacts with infected individuals, and recovery rate). A long–run trend analysis for 1 year was simulated. The results fit well to the current case data of the sample corona center. Effective preventive and reactive resource planning basically depends on accurately designed models, tools, and techniques needed for the prediction of feature threats, risks, and mitigation costs. In order to sufficiently analyze the transmission and recovery dynamics of epidemics it is important to choose concise mathematical models. Hence, a unique stochastic modeling approach tied to queueing theory and computer simulation has been chosen. The methods used here can also serve as a guidance for accurate modeling and classification of stages (or compartments) of epidemics in general.

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Section: Infection To Quarantinementioning

confidence: 99%

Building epidemic models for living populations and computer networks

Kondakci¹,

Kondakci²

2021

Science Progress

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“…As stated in Martin del Rey [15], the first mathematical model studies aimed at predicting the behavior of an epidemic of were carried out in time Kephart and White [16,17,18]. Mishra and Saini [19] developed an SEIRS model of computer malware in which they assume that any computer in the network is susceptible to malware infection.…”

Section: Related Literaturesmentioning

confidence: 99%

Epidemic Model and Mathematical Study of Impact of Vaccination for the Control of Malware in Computer Network

Chinebu¹,

Udegbe

Eberendu

2021

JAMCS

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Malware remains a significant threat to computer network. In this paper, we consideredthe problem which computer malware cause to personal computers with its control by proposing a compartmental model SVEIRS (Susceptible Vaccinated-Exposed-infected-Recovered-Susceptible) for malware transmission in computer network using nonlinear ordinary differential equation. Through the analysis of the model, the basic reproduction number were obtained, and the malware free equilibrium was proved to be locally asymptotical stable if is less than unity and globally asymptotically stable if Ro is less than some threshold using a Lyapunov function. Also, the unique endemic equilibrium exists under certain conditions and the model underwent backward bifurcation phenomenon. To illustrate our theoretical analysis, some numerical simulation of the system was performed with RungeKutta fourth order (KR4) method in Mathlab. This was used in analyzing the behavior of different compartments of the model and the results showed that vaccination and treatment is very essential for malware control.

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“…Such works are very few in number, and they are usually devoted to solving certain narrow tasks in the field of information security. Thus, there are known works [22][23][24][25] devoted to the research of computer viruses and malware evolution-both in terms of the program structure itself and in terms of the speed of infecting system components. For example, in [23], the authors use an evolutionary approach to describe a change in the dynamic behavior of polymorphic worms, a family of computer viruses capable of changing their own structure, which makes them extremely difficult to detect.…”

Section: Related Workmentioning

confidence: 99%

Cyber Attack Prevention Based on Evolutionary Cybernetics Approach

et al. 2020

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The paper looks at the problem of cybersecurity in modern cyber–physical systems and proposes an evolutionary model approach to counteract cyber attacks by self-regulating the structure of the system, as well as several evolutionary indicators to assess the state of the system. The application of evolutionary models makes it possible to describe the regularities of systems behavior and their technical development, which is especially important regarding cyber attacks, which are the cause of a discontinuous evolution of complex systems. A practical example describes a system behavior during attacks and the self-regulation of its structure. The methodological approach consists of using evolutionary models to describe how modern cyber–physical systems can counteract cyber attacks and evolve, building on the experience of past security incidents. The main conclusions and recommendations are presented in the Discussion section, and they consist of the fact that using an evolutionary approach will not only increase the security of cyber–physical systems, but also define the principles of building systems that are resistant to cyber attacks.

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Mathematical modeling of the propagation of malware: a review

Cited by 79 publications

References 75 publications

Building epidemic models for living populations and computer networks

Building epidemic models for living populations and computer networks

Epidemic Model and Mathematical Study of Impact of Vaccination for the Control of Malware in Computer Network

Cyber Attack Prevention Based on Evolutionary Cybernetics Approach

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