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Exploring Efficient and Robust Virtual Machine Introspection Techniques

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Algorithms and Architectures for Parallel Processing (ICA3PP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9530))

Abstract

Upon practical implementation of virtual machine introspection (VMI), administrators may be overwhelmed by dozens of research works. Specifically, the adopted introspection mechanism perform differently with regard to various performance and security requirements. Besides, most of previous works do not clarify the boundary between Trusted Computing Base (TCB) and attacks towards introspection. This paper aims to help administrators to determine the appropriate introspection approach. Firstly, we summarize current VMI technologies, and present a classification method mainly depending on whether hardware assistance is required, how it solves the semantic gap problem and how introspection is triggered. Secondly, we discuss how to achieve a good trade-off between the two metrics of performance and security. Thirdly, we propose a TCB threat model to employ VMI along with other enhancing mechanism to tackle attacks in different levels of TCB. Finally, we discuss some future trends related to VMI for further improving security.

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Notes

  1. 1.

    Hypervisor is also referred to “Virtual Machine Monitor” (VMM), we do not differentiate them in this paper.

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Acknowledgement

We would like to thank the anonymous reviewers for their valuable comments and help in improving this paper. This work is supported by China National Key Technology Support Program (2012BAH46B02).

Author information

Authors and Affiliations

  1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    Chonghua Wang, Xiaochun Yun, Zhiyu Hao, Lei Cui, Yandong Han & Qingxin Zou

  2. School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China

    Chonghua Wang & Yandong Han

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  1. Chonghua Wang
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  2. Xiaochun Yun
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  3. Zhiyu Hao
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Correspondence to Zhiyu Hao .

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Editors and Affiliations

  1. Central South University, Changsha, China

    Guojun Wang

  2. The University of Sydney, Sydney, New South Wales, Australia

    Albert Zomaya

  3. University of Murcia, Murcia, Murcia, Spain

    Gregorio Martinez

  4. Hunan University, Changsha, China

    Kenli Li

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Wang, C., Yun, X., Hao, Z., Cui, L., Han, Y., Zou, Q. (2015). Exploring Efficient and Robust Virtual Machine Introspection Techniques. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9530. Springer, Cham. https://doi.org/10.1007/978-3-319-27137-8_32

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