发明授权
US08844033B2 Systems, methods, and media for detecting network anomalies using a trained probabilistic model
有权
使用训练有素的概率模型检测网络异常的系统，方法和媒体
- 专利标题： Systems, methods, and media for detecting network anomalies using a trained probabilistic model
- 专利标题（中）： 使用训练有素的概率模型检测网络异常的系统，方法和媒体
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申请号： US12994550申请日： 2009-05-27
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公开(公告)号： US08844033B2公开(公告)日： 2014-09-23
- 发明人: Yingbo Song , Angelos D. Keromytis , Salvatore J. Stolfo
- 申请人： Yingbo Song , Angelos D. Keromytis , Salvatore J. Stolfo
- 申请人地址： US NY New York
- 专利权人： The Trustees of Columbia University in the City of New York
- 当前专利权人： The Trustees of Columbia University in the City of New York
- 当前专利权人地址： US NY New York
- 代理机构： Byrne Poh LLP
- 国际申请： PCT/US2009/045242 WO 20090527
- 国际公布： WO2010/011411 WO 20100128
- 主分类号： G06F21/00
- IPC分类号： G06F21/00 ; H04L29/06 ; H04L29/08
摘要：
Systems, methods, and media for detecting network anomalies are provided. In some embodiments, a training dataset of communication protocol messages having argument strings is received. The content and structure associated with each of the argument strings is determined and a probabilistic model is trained using the determined content and structure of each of the argument strings. A communication protocol message having an argument string that is transmitted from a first processor to a second processor across a computer network is received. The received communication protocol message is compared to the probabilistic model and then it is determined whether the communication protocol message is anomalous.
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