Abstract
The normal operation of virtual machine is a necessity for supporting cloud service. Motivated by the great desire of automated abmornal operation detection, this paper proposes a Hidden Markov Model-based method to conduct anomaly detection of virtual machine. This model can depict normal outline base of virtual machine operation and detect system outliers through calculating non-match rate. Through verifying the method in a real distributed environment, experiment results indicate that this method has 1.1%–4.9% better detection accuracy compared with two leading benchmarks with a much better efficiency.
| Original language | English |
|---|---|
| Title of host publication | Provable Security - 13th International Conference, ProvSec 2019 Cairns, QLD, Australia, October 1–4, 2019 Proceedings |
| Editors | Ron Steinfeld, Tsz Hon Yuen |
| Place of Publication | Cham Switzerland |
| Publisher | Springer |
| Pages | 372-380 |
| Number of pages | 9 |
| ISBN (Electronic) | 9783030319199 |
| ISBN (Print) | 9783030319182 |
| DOIs | |
| Publication status | Published - 2019 |
| Event | International Conference on Provable Security 2019 - Cairns, Australia Duration: 1 Oct 2019 → 4 Oct 2019 Conference number: 13th https://www.monash.edu/provsec2019 https://link.springer.com/book/10.1007/978-3-030-31919-9 (Proceedings) |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer |
| Volume | 11821 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | International Conference on Provable Security 2019 |
|---|---|
| Abbreviated title | ProvSec 2019 |
| Country/Territory | Australia |
| City | Cairns |
| Period | 1/10/19 → 4/10/19 |
| Internet address |
Keywords
- Anomaly detection
- Cloud computing
- Hidden Markov Model
- Virtual machine