Exploring Efficient and Robust Virtual Machine Introspection Techniques

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.