A4 Refereed article in a conference publication
Virtual Machine Introspection based Cloud Monitoring Platform
Authors: Samuel Laurén, Ville Leppänen
Editors: Boris Rachev, Angel Smrikarov
Conference name: International Conference on Computer Systems and Technologies
Publishing place: New York, NY
Publication year: 2018
Book title : CompSysTech'18: 19th International Conference on Computer Systems and Technologies
Series title: ICPS: ACM International Conference Proceeding Series
Number in series: 1641
First page : 104
Last page: 109
ISBN: 978-1-4503-6425-6
DOI: https://doi.org/10.1145/3274005.3274030(external)
Web address : https://dl.acm.org/citation.cfm?id=3274030(external)
Virtual Machine Introspection (VMI) is an
emerging family of techniques for extracting data from virtual machines
without the use of active monitoring probes within the target machines
themselves. In VMI based systems, the data is collected at the
hypervisor-level by analyzing the state of virtual machines. This has
the benefit of making collection harder to detect and block by malware
as there is nothing in the machine indicating that monitoring is taking
place.
In this paper we present Nitro Web, a web-based monitoring
system for virtual machines that uses virtual machine introspection for
data collection. The platform is capable of detecting and visualizing
system call activity taking place within virtual machines in real-time.
The
secondary purpose of this paper is to offer an introduction to Nitro
virtual machine introspection framework that we have been involved in
developing. In this paper, we reflect on how Nitro Framework can be used
for building applications making use of VMI data.