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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Software . 2026
Data sources: ZENODO
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Software . 2026
Data sources: Datacite
ZENODO
Software . 2026
Data sources: Datacite
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Goodkit - Framework for Virtual Machine Introspection

Authors: Teguia, Dufy; Tchana, Alain; Lazri, Kahina; Lachaize, Renaud;

Goodkit - Framework for Virtual Machine Introspection

Abstract

We present GOODKIT, a new framework for live virtual machine introspection (LVMI) designed for performance, scalability, and safe integration in modern cloud environments. GOODKIT executes observers as lightweight VMs colocated with the VMM, enabling native-speed access to the target state while preserving strong isolation. GOODKIT introduces fine-grained, lock-aware memory coherence mechanisms, a configurable probing subsystem for I/O and kernel-level events, and a mutualization layer that allows multiple observers to operate concurrently without degrading target performance. Across 21 real world usecases, including rootkit detection, ransomware monitoring, and scheduler introspection, GOODKIT delivers high performance strong isolation, and broad applicability.

Keywords

virtualization, VMI, Firecracker

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average