A multi-dimensional trustworthy behavior monitoring method based on discriminant locality preserving projections

Authors:
Guanghui Chang;Shuyu Chen;Huawei Lu;Xiaoqin Zhang
Affiliations:
College of Computer Science, Chongqing University, Chongqing, China;School of Software Engineering, Chongqing University, Chongqing, China;College of Computer Science, Chongqing University, Chongqing, China;College of Computer Science, Chongqing University, Chongqing, China
Venue:
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Year:
2010

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Abstract

Trustworthy decision is a key step in trustworthy computing, and the system behavior monitoring is the base of the trustworthy decision. Traditional anomaly monitoring methods describe a system by using single behavior feature, so it's impossible to acquire the overall status of a system. A new method, called discriminant locality preserving projections (DLPP), is proposed to monitor multi-dimensional trustworthy behaviors in this paper. DLPP combines the idea of Fisher discriminant analysis (FDA) with that of locality preserving projections (LPP). This method is testified by events injection, and the experimental results show that DLPP is correct and effective.