A Non-Cooperative Resource Utilization Game Between Two Competing Malware

被引:5
作者
Varma, Vineeth S. [1 ]
Hayel, Yezekayel [2 ]
Morarescu, Irinel-Constantin [1 ]
机构
[1] Univ Lorraine, CNRS, CRAN, F-54000 Nancy, France
[2] Univ Avignon, Dept Comp Sci, F-84911 Avignon, France
来源
IEEE CONTROL SYSTEMS LETTERS | 2022年 / 7卷
关键词
Malware; Games; Computational modeling; Resource management; Viruses (medical); Computer viruses; Statistics; Computer networks; game theory; compartmental models; PROPAGATION;
D O I
10.1109/LCSYS.2022.3186620
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this letter, we consider a population of digital nodes (such as phones, computers, etc.) that are under the attack of two competing malware. These malware infect the nodes in order to exploit their computational resources for specific purposes such as mining crypto-currency, cloud computing, etc. We suppose that each virus spreads following the susceptible-infected-susceptible (SIS) compartmental model. Additionally, we assume that the malware designers can tune the percentage of resource utilization from their host nodes. A higher resource utilization implies a higher instantaneous profit but will also lead to faster detection and elimination (node recovery) of the malware. Once the malware is detected, complete protection of the infected node by means of anti-malware software is also possible at a smaller rate. The proposed setup results in a non-cooperative game between the two players (the malware designers) trying to maximize their profit i.e., the resources utilized from the infected nodes. We characterize and analyze the Nash equilibrium for such a game using a time-scale separation approximation. Finally, we numerically validate the approximation and we compute the price of anarchy.
引用
收藏
页码:67 / 72
页数:6
相关论文
共 14 条
[1]  
Bailey N.T, 1975, The Mathematical Theory of Infectious Diseases and Its Applications
[2]   REACHING A CONSENSUS [J].
DEGROOT, MH .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1974, 69 (345) :118-121
[3]  
Fudenberg D., 1991, Game Theory, V393
[4]  
Hayel Y, 2014, IEEE DECIS CONTR P, P1179, DOI 10.1109/CDC.2014.7039541
[5]   Game-Theoretic Vaccination Against Networked SIS Epidemics and Impacts of Human Decision-Making [J].
Hota, Ashish R. ;
Sundaram, Shreyas .
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2019, 6 (04) :1461-1472
[6]   Intrusion detection: A brief history and overview [J].
Kemmerer, D ;
Vigna, G .
COMPUTER, 2002, :27-30
[7]  
Khalil H. K., 2008, Nonlinear Systems, V3rd ed.
[8]   Analysis and Control of a Continuous-Time Bi-Virus Model [J].
Liu, Ji ;
Pare, Philip E. ;
Nedic, Angelia ;
Tang, Choon Yik ;
Beck, Carolyn L. ;
Basar, Tamer .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2019, 64 (12) :4891-4906
[9]  
Masucci AM, 2014, ANN ALLERTON CONF, P951, DOI 10.1109/ALLERTON.2014.7028557
[10]   Smartphone Malware and Its Propagation Modeling: A Survey [J].
Peng, Sancheng ;
Yu, Shui ;
Yang, Aimin .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2014, 16 (02) :925-941