PUBLICACIÓN

New approaches of epidemic models to simulate malware propagation

ACCEDER A LA PUBLICACIÓN: Orcid

Hernández Guillén, J.D., Martín del Rey, Á., Hernández Encinas, L.

2018

DOI

10.1007/978-3-319-67180-2_61

EID

2-s2.0-85028637097

ISBN

21945357

BIBTEX

@article{Hernández Guillén2018,title = {New approaches of epidemic models to simulate malware propagation},journal = {Advances in Intelligent Systems and Computing},year = {2018},volume = {649},pages = {631-640},author = {Hern{\'a}ndez Guill{\'e}n, J.D. and Mart{\'i}n del Rey, ?. and Hern{\'a}ndez Encinas, L.}}

AUTORES DE LA UEX

Jose Diamantino Hernández Guillén

OTRAS PUBLICACIONES DE INTERÉS

Higher-Order Nonstandard Finite Difference Schemes For A Mseir Model For A Malware Propagation
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Propagation Of The Malware Used In Apts Based On Dynamic Bayesian Networks
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Propagation Of The Malware Used In Apts Based On Dynamic Bayesian Networks
A Mathematical Model For Malware Spread On Wsns With Population Dynamics
Propagation Of The Malware Used In Apts Based On Dynamic Bayesian Networks
A Mathematical Model For Malware Spread On Wsns With Population Dynamics
Security Countermeasures Of A Sciras Model For Advanced Malware Propagation
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Security Countermeasures Of A Sciras Model For Advanced Malware Propagation
Study Of The Malware Scirs Model With Different Incidence Rates
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Variable Step Length Algorithms With High-Order Extrapolated Non-Standard Finite Difference Schemes For A Seir Model
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New Approaches Of Epidemic Models To Simulate Malware Propagation
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Modeling Malware Propagation Using A Carrier Compartment
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Modeling Malware Propagation Using A Carrier Compartment
Study Of The Stability Of A Seirs Model For Computer Worm Propagation
Modeling Malware Propagation Using A Carrier Compartment
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Higher-Order Nonstandard Finite Difference Schemes For A Mseir Model For A Malware Propagation
Study Of The Stability Of A Seirs Model For Computer Worm Propagation
Higher-Order Nonstandard Finite Difference Schemes For A Mseir Model For A Malware Propagation
Improving Safety Awareness Campaigns Through The Use Of Graph Neural Networks
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