Dancing with wolves: Towards practical event-driven VMM monitoring

Liang Deng, Peng Liu, Jun Xu, Ping Chen, Qingkai Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

This paper presents a novel framework that enables practical event-driven monitoring for untrusted virtual machine monitors (VMMs) in cloud computing. Unlike previous approaches for VMM monitoring, our framework neither relies on a higher privilege level nor requires any special hardware support. Instead, we place the trusted monitor at the same privilege level and in the same address space with the untrusted VMM to achieve superior efficiency, while proposing a unique mutual-protection mechanism to ensure the integrity of the monitor. Our security analysis demonstrates that our framework can provide high-assurance for event-driven VMM monitoring, even if the highest-privilege VMM is fully compromised. The experimental results show that our framework only incurs trivial performance overhead for enforcing event-driven monitoring policies, exhibiting tremendous performance improvement on previous approaches.

Original languageEnglish (US)
Title of host publicationVEE 2017 - Proceedings of the 2017 ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments
PublisherAssociation for Computing Machinery, Inc
Pages83-96
Number of pages14
ISBN (Electronic)9781450349482
DOIs
StatePublished - Apr 8 2017
Event2017 ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, VEE 2017 - Xi'an, China
Duration: Apr 8 2017Apr 9 2017

Publication series

NameVEE 2017 - Proceedings of the 2017 ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments

Other

Other2017 ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, VEE 2017
CountryChina
CityXi'an
Period4/8/174/9/17

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Software

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