Study of the stability of a SEIRS model for computer worm propagation

被引:38
作者
Hernandez Guillen, J. D. [1 ]
Martin del Rey, A. [2 ]
Hernandez Encinas, L. [3 ]
机构
[1] Univ Salamanca, Dept Appl Math, Calle Parque 2, E-37008 Salamanca, Spain
[2] Univ Salamanca, Inst Fundamental Phys & Math, Dept Appl Math, Calle Parque 2, E-37008 Salamanca, Spain
[3] CSIC, Spanish Natl Res Council, Inst Phys & Informat Technol, C Serrano 144, Madrid 28006, Spain
关键词
Malware propagation; Mathematical model; Stability analysis; Computer worms; Basic reproductive number; GLOBAL-STABILITY; TRANSMISSION;
D O I
10.1016/j.physa.2017.03.023
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Nowadays, malware is the most important threat to information security. In this sense, several mathematical models to simulate malware spreading have appeared. They are compartmental models where the population of devices is classified into different compartments: susceptible, exposed, infectious, recovered, etc. The main goal of this work is to propose an improved SEIRS (Susceptible Exposed Infectious Recovered Susceptible) mathematical model to simulate computer worm propagation. It is a continuous model whose dynamic is ruled by means of a system of ordinary differential equations. It considers more realistic parameters related to the propagation; in fact, a modified incidence rate has been used. Moreover, the equilibrium points are computed and their local and global stability analyses are studied. From the explicit expression of the basic reproductive number, efficient control measures are also obtained. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:411 / 421
页数:11
相关论文
共 16 条
[1]  
Anderson Ross., 2013, EC INFORM SECURITY P, DOI DOI 10.1007/978-3-642-39498-0_12
[2]  
DIEKMANN O, 1990, J MATH BIOL, V28, P365
[3]  
Freedman HI., 1994, J DYN DIFFER EQU, V6, P583, DOI [10.1007/BF02218848, DOI 10.1007/BF02218848]
[4]   Malware propagation modeling considering software diversity and immunization [J].
Hosseini, Soodeh ;
Azgomi, Mohammad Abdollahi ;
Rahmani, Adel Torkaman .
JOURNAL OF COMPUTATIONAL SCIENCE, 2016, 13 :49-67
[5]  
Hurwitz A., 1895, Mathematische Annalen, V46, P273, DOI [10.1007/BF01446812, DOI 10.1007/BF01446812]
[6]  
Karyotis V., 2016, Malware Diffusion Models for Modern Complex Networks: Theory and Applications
[7]  
LASALLE JP, 1976, REGIONAL C SERIES AP, V25
[8]   A geometric approach to global-stability problems [J].
Li, MY ;
Muldowney, JS .
SIAM JOURNAL ON MATHEMATICAL ANALYSIS, 1996, 27 (04) :1070-1083
[9]   Mathematical modeling of the propagation of malware: a review [J].
Martin del Rey, Angel .
SECURITY AND COMMUNICATION NETWORKS, 2015, 8 (15) :2561-2579
[10]  
Masud M, 2012, DATA MINING TOOLS FOR MALWARE DETECTION, P1