Modeling Passive Propagation of Malwares on the WWW

Liu, Chunbo; Jia, Chunfu

doi:10.1016/j.phpro.2012.05.062

Cited by 3 publications

(3 citation statements)

References 10 publications

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“…In recent times epidemiological researchers of network security have highlighted the sameness in connectivity realities between biological viruses and malware equivalents. This has resulted to the use of epidemic models for the understanding of malware spread in networks (computer networks [4], peer-to-peer (P2P) [5], wireless sensor networks [6] and the WWW [7] or the internet [8]). These epidemic models compartmentalize the hosts according to their disease/infection status.…”

Section: Related Workmentioning

confidence: 99%

Modeling Multigroup Malicious Code Infections in Sensor Networks

Nwokoye¹,

Onyesolu²

2018

IJCA

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Older epidemic models of wireless sensor network (WSN) mostly cater for one type of malicious code infection. Inspired by the modeling of heterogeneous populations of diseases in the Biosciences, we propose the Susceptible, Infectious due to virus, Infectious due to worm, Infectious due to a virus/worm variant, Recovered and Susceptible with Vaccination (SIjRS-V) epidemic model, to characterize the dynamics of propagation of more than one malicious code infection in a WSN. Aside possessing differential infectivity, the proposed model has transmission range and densitycharacteristic features of a WSN. We discovered that the actual reproduction number ( ) involves the infective and death rates of virus, worm and a virus/worm variant as well as the communication range and density. In other words, the actual is the sum of the 'reproduction numbers' for each group. A numerical method was used to solve the system of equations. The impact of transmission range and distribution density on the different types of malicious codes was investigated using simulation experiments.

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Section: Related Workmentioning

confidence: 99%

Modeling Multigroup Malicious Code Infections in Sensor Networks

Nwokoye¹,

Onyesolu²

2018

IJCA

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“…Usually referred to as "Epidemic models", these system(s) of equations that implement the epidemic theory can be ordinary differential, partial differential, or difference (depending on the intention of the modeler). Aside its application, in public health, they are also evident in the characterization of computer networks [11], peer-to-peer (P2P) [12], wireless sensor networks [13] and the WWW [14] or the internet [15].…”

Section: Related Workmentioning

confidence: 99%

Modeling the effect of Network Access Control and Sensor Random Distribution on Worm Propagation

Nwokoye¹,

Mbeledogu²,

Umeh³

et al. 2017

IJMECS

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Abstract-Sensor networks are appealing targets for malicious attacks that invade the network with the aim of depleting the confidentiality, availability and integrity (CIA) features/parameters of neighboring sensor nodes. This is due to its open communication, minimal resources and its deployment in un-trusted, unguarded and unfriendly terrains. To restrict illegitimate users or malicious attackers (such as worms) network analysts have suggested network access control (NAC). Specifically, we apply NAC to wireless sensor network epidemic models in order to investigate distribution density, transmission range and sensor area/field. Our analyses involved analytical expressions of two sensor fields gleaned from literature. Additionally, we explored the possibilities of infectivity of sensor nodes at the exposed class using the two expressions for sensor field topologies. We also derived the reproduction ratios and solutions at several equilibrium points for the models. It is our hope that that our work herein would impact sensor deployment decisions for organizations that utilize wireless sensor networks for meaningful daily activities.

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“…The effort of many scientists and mathematicians in the area of computer technology and its security is magnetized many authors. The projected model and its similar development are analysed by many scholars [48][49][50][51][52][53][54][55].…”

Section: Introductionmentioning

confidence: 99%

Etkili yöntem kullanan ağ erişim kontrolü modeli için kesirli yaklaşım

İlhan¹

2021

Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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In this paper, we find the solution for the system of nonlinear ordinary differential equations having fractional-order arising in network access control using fractional natural decomposition method (FNDM). The consider a model which consists of a system of five nonlinear ordinary differential equations (NODEs), which illustrate the sensor networks are interesting essentials for malicious outbreaks that attack the network with the intention of reducing the integrity, availability and confidentiality. Further, we captured the nature of FNDM results for different value of fractional order in terms of the plots. The considered scheme highly effective and structured while examining nonlinear models and which can be observed and confirm from the obtained results. Further, the conspiracies cited in plots confirm the hired fractional operator and algorithm can help to exemplify the more fascinating properties of the nonlinear system associated real-world problems.

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Modeling Passive Propagation of Malwares on the WWW

Cited by 3 publications

References 10 publications

Modeling Multigroup Malicious Code Infections in Sensor Networks

Modeling Multigroup Malicious Code Infections in Sensor Networks

Modeling the effect of Network Access Control and Sensor Random Distribution on Worm Propagation

Etkili yöntem kullanan ağ erişim kontrolü modeli için kesirli yaklaşım

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