Name
Abstract | ||
|---|---|---|
In the past, the concept of self-evolving botnets, where computing resources of infected hosts are exploited to discover vulnerabilities, have been introduced in the literature. This paper proposes a deterministic epidemic model that represents the infection dynamics of self-evolving botnets. The proposed epidemic model represents the infection dynamics of the self-evolving botnet with ordinary differential equations based on a Susceptible-Infected-Recovered-Susceptible model, which is widely used for general epidemic models of malware infection. Through numerical calculations, we show the infection behavior of self-evolving botnets. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICOIN.2019.8718173 | 2019 International Conference on Information Networking (ICOIN) |
Keywords | Field | DocType |
ordinary differential equations,susceptible-infected-recovered-susceptible model,infection behavior,malware infection,general epidemic models,deterministic epidemic model,infected hosts,self-evolving botnet,infection dynamics | Computer science,Botnet,Computer network,Distributed computing | Conference |
ISSN | ISBN | Citations |
1976-7684 | 978-1-5386-8351-4 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuya Kumai | 1 | 0 | 0.34 |
| Koki Hongyo | 2 | 0 | 0.68 |
| Tomotaka Kimura | 3 | 11 | 8.82 |
| Kouji Hirata | 4 | 10 | 11.28 |