Leveraging Static Probe Instrumentation for VM-based Anomaly Detection System
Autor: | Takeshi Okuda, Ady Wahyudi Paundu, Youki Kadobayashi, Suguru Yamaguchi |
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Rok vydání: | 2016 |
Předmět: |
Computer science
business.industry 020208 electrical & electronic engineering Real-time computing Hypervisor Feature selection Cloud computing 02 engineering and technology 021001 nanoscience & nanotechnology Proof of concept 0202 electrical engineering electronic engineering information engineering Overhead (computing) Anomaly detection Instrumentation (computer programming) Anomaly (physics) 0210 nano-technology business |
Zdroj: | Information and Communications Security ISBN: 9783319298139 ICICS |
DOI: | 10.1007/978-3-319-29814-6_27 |
Popis: | In this preliminary study, we introduce a framework to predict anomaly behavior from Virtual Machines (VMs) deployed in public IaaS cloud model. Within this framework we propose to use a static probe instrumentation technique inside hypervisor in order to collect monitoring data and a black-box signature based feature selection method using Linear Discriminant Analysis. As a proof of concept, we run several evaluation tests to measure the output quality and computation overhead of our Anomaly Detection System (ADS) using feature selection. The results show that our feature selection technique does not significantly reduce the anomaly prediction quality when compared with full featured ADS and gives a better accuracy when compared to ADS with system-call data. Furthermore, ADS with feature selection method creates lower computing overhead compared to the other two ADS. |
Databáze: | OpenAIRE |
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