A Multi-dimensional Trustworthy Behavior Monitoring Method Based on Discriminant Locality Preserving Projections

摘要：

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 its impossible to acquire the overall status of a system. A new method, called discriminant locality preserving projections (DLPP), is proposed to monitor multidimensional 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.

关键词： multi-dimensional trustworthy behavior monitoring anomalies discrimination discriminant locality preserving projections

作者: Guanghui Chang Shuyu Chen Huawei Lu Xiaoqin Zhang

作者单位: College of Computer Science, Chongqing University,Chongqing 400030, China College of Computer Science, Chongqing University,Chongqing 400030, China School of Software Enginee

会议类型: 国际会议

会议名称: 6th International Conference on Advanced Data Mining and Applications(第六届先进数据挖掘及应用国际会议 ADMA 2010)

会议地点: 重庆

会议语种:英文

页码: 435-442

在线出版日期: 2010-11-19（万方平台首次上网日期，不代表论文的发表时间）