Visible to the public Multi-Aspect, Robust, and Memory Exclusive Guest OS Fingerprinting

TitleMulti-Aspect, Robust, and Memory Exclusive Guest OS Fingerprinting
Publication TypeJournal Article
Year of Publication2014
AuthorsYufei Gu, Yangchun Fu, Prakash, A., Zhiqiang Lin, Heng Yin
JournalCloud Computing, IEEE Transactions on
Volume2
Pagination380-394
Date PublishedOct
ISSN2168-7161
Keywordscloud computing, code hash based approach, code signature approach, computer security, data structures, digital forensics, digital signatures, Fingerprint recognition, Forensics, kernel code aspect, kernel data signature, Linux, Linux kernels, memory exclusive guest OS fingerprinting, memory forensics, multiaspect memory exclusive approach, Operating system fingerprinting, operating system precise fingerprinting, OS-SOMMELIER, physical memory dump, virtual machine introspection, Virtual machining
Abstract

Precise fingerprinting of an operating system (OS) is critical to many security and forensics applications in the cloud, such as virtual machine (VM) introspection, penetration testing, guest OS administration, kernel dump analysis, and memory forensics. The existing OS fingerprinting techniques primarily inspect network packets or CPU states, and they all fall short in precision and usability. As the physical memory of a VM always exists in all these applications, in this article, we present OS-SOMMELIER+, a multi-aspect, memory exclusive approach for precise and robust guest OS fingerprinting in the cloud. It works as follows: given a physical memory dump of a guest OS, OS-SOMMELIER+ first uses a code hash based approach from kernel code aspect to determine the guest OS version. If code hash approach fails, OS-SOMMELIER+ then uses a kernel data signature based approach from kernel data aspect to determine the version. We have implemented a prototype system, and tested it with a number of Linux kernels. Our evaluation results show that the code hash approach is faster but can only fingerprint the known kernels, and data signature approach complements the code signature approach and can fingerprint even unknown kernels.

URLhttp://ieeexplore.ieee.org/document/6853383/
DOI10.1109/TCC.2014.2338305
Citation Key6853383