Name
Title | ||
|---|---|---|
Evaluation of countermeasure against future malware evolution with deterministic modeling |
Abstract | ||
|---|---|---|
Recently, machine learning technologies have dramatically evolved. Accordingly, the concept of self-evolving botnets has been introduced, which discover vulnerabilities of hosts by distributed machine learning using the computational resources of infected hosts, and infect other hosts by attacks using the discovered vulnerabilities. The infectability of the self-evolving botnets is too strong compared with conventional botnets, so that such new botnets will become the serious threat to future network society including SG and IoT environments. In this paper, we consider a volunteer model that discovers unknown vulnerabilities earlier than self-evolving botnets by distributed computing using volunteer hosts' resources and repairs the vulnerabilities. We propose deterministic modeling for the volunteer model. Through numerical calculations, we evaluate the performance of the volunteer model against self-evolving botnets. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/APSIPAASC47483.2019.9023350 | Asia-Pacific Signal and Information Processing Association Annual Summit and Conference |
DocType | ISSN | Citations |
Conference | 2309-9402 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Koki Shimizu | 1 | 0 | 0.34 |
| Yuya Kumai | 2 | 0 | 0.34 |
| Kimiko Motonaka | 3 | 0 | 0.34 |
| Tomotaka Kimura | 4 | 11 | 8.82 |
| Kouji Hirata | 5 | 10 | 11.28 |