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Cited by 313

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

NOVA: a microhypervisor-based secure virtualization architecture

Open access
Steinberg, Udo, Kauer, Bernhard·2010·Proceedings of the 5th European conference on Computer systems

Abstract

The availability of virtualization features in modern CPUs has reinforced the trend of consolidating multiple guest operating systems on top of a hypervisor in order to improve platform-resource utilization and reduce the total cost of ownership. However, today's virtualization stacks are unduly large and therefore prone to attacks. If an adversary manages to compromise the hypervisor, subverting the security of all hosted operating systems is easy. We show how a thin and simple virtualization layer reduces the attack surface significantly and thereby increases the overall security of the system. We have designed and implemented a virtualization architecture that can host multiple unmodified guest operating systems. Its trusted computing base is at least an order of magnitude smaller than that of existing systems. Furthermore, on recent hardware, our implementation outperforms contemporary full virtualization environments.

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Crossref · 10.1145/1755913.1755935

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Metadata

Authors
Steinberg, U., & Kauer, B.
Venue
Proceedings of the 5th European conference on Computer systems
Publisher
ACM
Published
2010-04-13
Pages
209-222
OpenAlex
W2100678175
Cited by
313
References
27
FWCI
25.73
Type
conference paper
Language
en
Open access
green

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CoChat. (2026). Citation check: NOVA: a microhypervisor-based secure virtualization architecture. https://app.cochat.ai/papers/10.1145/1755913.1755935
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Steinberg, U., & Kauer, B. (2010). NOVA: a microhypervisor-based secure virtualization architecture. Proceedings of the 5th European conference on Computer systems. https://doi.org/10.1145/1755913.1755935

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.