Modeling and control of computer virus attack on a targeted network

Upadhyay, Ranjit Kumar; Singh, Prerna

doi:10.1016/j.physa.2019.122617

Cited by 13 publications

(5 citation statements)

References 16 publications

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“…In [9], a model with two different structures-attacking class and target class-is presented to study the mobility of viruses when attacking a target network. The concept of optimal control is introduced to regulate the spread of the virus, and the use of a firewall is also suggested.…”

Section: Backroundmentioning

confidence: 99%

Modelling Artificial Immunization Processes to Counter Cyberthreats

2021

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This paper looks at the problem of cybersecurity in modern cyber-physical and information systems and proposes an immune-like approach to the information security of modern complex systems. This approach is based on the mathematical modeling in information security—in particular, the use of immune methods to protect several critical system nodes from a predetermined range of attacks, and to minimize the success of an attack on the system. The methodological approach is to systematize the tasks, means and modes of immunization to describe how modern systems can counter the spread of computer attacks. The main conclusions and recommendations are that using an immunization approach will not only improve the security of systems, but also define principles for building systems that are resistant to cyber attacks. The immunization approach enables a symmetrical response to an intruder in a protected system to be produced rapidly. This symmetry provides a step-by-step neutralization of all stages of a cyber attack, which, combined with the accumulation of knowledge of the attacker’s actions, allows a base of defensive responses to be generated for various cyber attack scenarios. The theoretical conclusions are supported by practical experiments describing real-world scenarios for the use of immunization tools to protect against cyber threats.

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Section: Backroundmentioning

confidence: 99%

Modelling Artificial Immunization Processes to Counter Cyberthreats

2021

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“…The result is affirming to the claim of M. Zhang et al [18] that large-scale and rapid virus dissemination occurs during the most frequent access to emails. As Upadhyay et al [5] puts it, if susceptible computers come into contact with infected computers, the virus can spread swiftly…”

Section: Simulationmentioning

confidence: 99%

“…In most circumstances, this could result in severe crises like concens about security. Therefore, it is very important to understand how malware spreads and affects the networks [5], [6]. In the era of information and communication technology (ICT) systems, everyone thinks as to how life is going to be carried out as ICT and communication devices play a crucial role in the different fields of our daily life particularly in this time of pandemic crisis.…”

Section: Introductionmentioning

confidence: 99%

Modeling virus spread on a network using NetLogo for optimum network management

Alimboyong

2021

IJEECS

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<span>The infections in computer networks are complex. Its spread is analogous to a contagious disease which can cause destruction within a few seconds. Viruses in a computer or computer networks can spread rapidly by various means such as access to online social networking sites like twitter, Facebook, and opening of email attachments. Thus, infections can go from being little dangerous to significantly harmful for a network. This paper proposed a simulation model that can predict the propagation of virus including the trend and the average infection rate using NetLogo software. Observed and simulated data sets were validated using chi-square tests. Results of the experiment have demonstrated accurate performance of the proposed model. The model could be very helpful for network administrators in mitigating the virus propagation and obstruct the spread of computer virus other than the usual prevention scheme particularly the use of antivirus software and inclusion of firewall security. </span>

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“…Meanwhile, in [12,13], antidotal computers are expressed as a separate compartment generating an SAIR model. Recently, Upadhyay and Singh [18] proposed a model with two different classes of computer nodes, the attacking and targeting nodes. They studied the virus propagation from an attack node into the targeted system.…”

Section: Introductionmentioning

confidence: 99%

A dynamic model of viruses with the effect of removable media on a computer network with heterogeneous immunity

Al-Tuwairqi

Bahashwan

2020

Adv Differ Equ

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In this paper, we build a mathematical model to study the impact of external removable devices on a network with weakly- and strongly-protected computers. The model describes the dynamics between weak, strong, infected computers and susceptible, infected removable media. Analytical investigations of the model produce two equilibrium points: virus-free and endemic. Moreover, we investigate the local and global stability of both equilibria. The existence and stability conditions of the equilibrium points depend primarily on the basic reproduction number ($R_{0}$R0) of the model. Furthermore, we perform numerical simulations to substantiate the analytical results. Also, a sensitivity analysis is carried out to examine the critical parameters that lead to strategies to control the dissipation of viruses.

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Modeling and control of computer virus attack on a targeted network

Cited by 13 publications

References 16 publications

Modelling Artificial Immunization Processes to Counter Cyberthreats

Modelling Artificial Immunization Processes to Counter Cyberthreats

Modeling virus spread on a network using NetLogo for optimum network management

A dynamic model of viruses with the effect of removable media on a computer network with heterogeneous immunity

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