A Fingerprinting System Calls Approach for Intrusion Detection in a Cloud Environment
Result description
Cloud Computing envisioned as the next generation architecture for IT enterprises, has proliferated itself due to the advantages it provides. Cloud Computing provides solutions for carrying out efficient, scalable and low cost computing. Due to the distributed nature of cloud based system, it is vulnerable to a large category of attacks out of which VM based attacks are most common. To counter these attacks we need Intrusion Detection System (IDS), which is used to monitor network traffic and policy violations from unauthorized users. Anomaly Detection is a technique of Intrusion Detection, which is used to detect intrusions by monitoring system activity and finding out patterns that do not comply with the normal behavior. In this paper an approach foranomaly detection in cloud environment is presented, which is based upon analysis of system call sequences generated by the virtual machines to the hypervisor. Our proposed implementation prevents malicious VM users to modify well known
Keywords
The result's identifiers
Result code in IS VaVaI
Result on the web
DOI - Digital Object Identifier
Alternative languages
Result language
angličtina
Original language name
A Fingerprinting System Calls Approach for Intrusion Detection in a Cloud Environment
Original language description
Cloud Computing envisioned as the next generation architecture for IT enterprises, has proliferated itself due to the advantages it provides. Cloud Computing provides solutions for carrying out efficient, scalable and low cost computing. Due to the distributed nature of cloud based system, it is vulnerable to a large category of attacks out of which VM based attacks are most common. To counter these attacks we need Intrusion Detection System (IDS), which is used to monitor network traffic and policy violations from unauthorized users. Anomaly Detection is a technique of Intrusion Detection, which is used to detect intrusions by monitoring system activity and finding out patterns that do not comply with the normal behavior. In this paper an approach foranomaly detection in cloud environment is presented, which is based upon analysis of system call sequences generated by the virtual machines to the hypervisor. Our proposed implementation prevents malicious VM users to modify well known
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2012 4th International Conference on Computational Aspects of Social Networks, CASoN 2012 : 21 ? 23 November 2012, S?o Carlos, Brazil
ISBN
978-1-4673-4793-8
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
309-314
Publisher name
IEEE
Place of publication
New York
Event location
Sao Carlos
Event date
Nov 21, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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Basic information
Result type
D - Article in proceedings
CEP
IN - Informatics
Year of implementation
2012