In this work, we assume an underlying x86 architecture running a hypervisor with two kinds of virtual machines: monitored guest virtual machine (GVM) and security virtual machine (SVM) in which our tools will be deployed.
In our work, the rootkit has root privilege access to compromise arbitrary entity and facility inside the GVM, including OS itself and applications.
After the task of intrusion detection starts, the Physical Memory Location Module firstly locates the hardware position of the current processes and the loaded modules in the GVM. Then the Semantic View Generation Module starts to build the high-level semantic view of GVM by parsing the physical memory through the Static Library generated by the BackDriver.
It extracts the semantic information of OS internals (including running process list, system call and loaded modules) of GVM by compiling kernel, then encapsulates all these information into a static library and provides standard call interfaces.
In the following, we describe the implementation details, with a focus on GVM state procurement and semantic view reconstruction.
The raw memory allocated to GVM can be procured by way of hypervisor.
GVMs are not without uncertainties and limitations when projecting the future distribution of ecosystems.
Three equilibrium doubled-carbon-dioxide GCM scenarios from the IPCC First Assessment Report (IPCC 1990: United Kingdom Met Office (UKMO), Geophysical Fluid Dynamics Laboratory (GFDL-R30) and Goddard Institute for Space Studies (GISS)) and two transient GCM scenarios from the IPCC Second Assessment Report (SAR) (IPCC 1996: (The Second Hadley Centre coupled ocean-atmosphere GCM)) HadCM2-ghg and (Max Planck Institute) (MPI-T106) were used to project vegetation change using the two GVMs. The climate-change scenarios, control climate and interpolation procedures (to a 0.5 [degrees] latitude-longitude resolution) are fully described in a study by Neilson (1998).
Because the older equilibrium GCM scenarios generally projected greater climate change (see UKMO in Table 2), they serve as useful proxies to illustrate the possible magnitude of vegetation change that may result from the upper range of the newly available SRES-based climate-change projections (i.e., AIF1, AIB or A2 scenarios in IPCC 2001a), which have not yet been combined with GVMs to explore the implications for vegetation change in North America.
The spatial distribution of potential vegetation as modelled by the MAPSS and BIOME3 GVMs under current climate (1961-1990) and future climate-change scenarios are presented in Figures 1 and 2 for comparison.
A comparison of the HadCM2 climate-change scenario, which was the only common climate-change scenario available for the MAPSS and BIOME3 GVMs, revealed that the BIOME3 consistently projected greater biome-type change compared with MAPSS.
The terrestrial grids of each GVM model were converted to shape files (polygons) in the Arcview 3.1 Geographic Information System (GIS).