ISCAS OpenIR
virtualization detection based on data fusion
Wang Jia-Bin; Lian Yi-Feng; Chen Kai
2012
Conference Name2012 International Conference on Computer Science and Information Processing, CSIP 2012
SourceProceedings - 2012 International Conference on Computer Science and Information Processing, CSIP 2012
Pages393-396
Conference DateAugust 24, 2012 - August 26, 2012
Conference PlaceXi'an, Shaanxi, China
Indexed TypeEI
ISBN9781467314114
Department(1) State Key Laboratory of Information Security Institute of Software Chinese Academy of Sciences Beijing China
English AbstractCharacteristic analysis and timing analysis are two methods for virtualization detection. However, the accuracy of characteristic analysis is low and the timing analysis is not efficient. Moreover, current methods based on timing analysis make use of the privileged instructions separately without data fusion and the accuracy of timing analysis can be improved further. In this paper, we introduce a new method in timing analysis based on data fusion to improve the accuracy of virtualization detection. Our method combines characteristic analysis and timing analysis, which makes virtualization detection more efficient. A virtualization detection tool is implemented and several experiments are made. The results show that our method is both effective and efficient. © 2012 IEEE.; Characteristic analysis and timing analysis are two methods for virtualization detection. However, the accuracy of characteristic analysis is low and the timing analysis is not efficient. Moreover, current methods based on timing analysis make use of the privileged instructions separately without data fusion and the accuracy of timing analysis can be improved further. In this paper, we introduce a new method in timing analysis based on data fusion to improve the accuracy of virtualization detection. Our method combines characteristic analysis and timing analysis, which makes virtualization detection more efficient. A virtualization detection tool is implemented and several experiments are made. The results show that our method is both effective and efficient. © 2012 IEEE.
KeywordComputer Science Data Fusion
SponsorshipXi'an Technological University; IEEE Xi'an Section; Missouri Western State University; Natl. New Netw. Monit. Control Eng. Lab.
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/15839
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Wang Jia-Bin,Lian Yi-Feng,Chen Kai. virtualization detection based on data fusion[C],2012:393-396.
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