
Nowadays, the vulnerability of cloud environment exposed in security places Virtual Machine Introspection(VMI) at risk: once attackers subvert any layers of cloud environment, such as host, virtual machine manager(VMM) or qemu, VMI will be exposed undoubtedly to those attackers too. Nearly all existing VMI techniques implicitly assume that both VMM by which VMI accesses specific VM data and host which VMI is running on, are nonmalicious and immutable. Unfortunately, this assumption can be potentially violated with the growing shortage of security in cloud environment. Once VMM or host is exploited, attackers can tamper the code or hijack the data of VMI, then, falsify VM information and certifications to Cloud system's administrators who try to make sure the security of specific VM in certain compute node. This paper proposes a new trusted VMI monitor frame: T-VMI, which can avoid the malicious subversion of the routine of VMI. T-VMI guarantees the integrity of VMI code using isolation and the correctness of VMI data using high privilege level instruction and appropriate trap mechanism. This model is evaluated on a simulation environment by using ARM Foundation Model 8.0 and has been presented on a real development ARMv8 JUNO-r0 board. We finished the comprehensive experiments including effectiveness and performance, and the result and analysis show T-VMI has achieved the aim of expected effectiveness with acceptable performance cost.
| 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). | 13 | |
| 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. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
