Invention Grant
US09253201B2 Detecting network anomalies by probabilistic modeling of argument strings with markov chains
有权
通过使用马尔可夫链的参数串的概率建模来检测网络异常
- Patent Title: Detecting network anomalies by probabilistic modeling of argument strings with markov chains
- Patent Title (中): 通过使用马尔可夫链的参数串的概率建模来检测网络异常
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Application No.: US14476142Application Date: 2014-09-03
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Publication No.: US09253201B2Publication Date: 2016-02-02
- Inventor: Yingbo Song , Angelos D. Keromytis , Salvatore J. Stolfo
- Applicant: Yingbo Song , Angelos D. Keromytis , Salvatore J. Stolfo
- Applicant Address: US NY New York
- Assignee: The Trustees of Columbia University in the City of New York
- Current Assignee: The Trustees of Columbia University in the City of New York
- Current Assignee Address: US NY New York
- Agency: Byrne Poh LLP
- Main IPC: H04L29/06
- IPC: H04L29/06 ; H04L29/08

Abstract:
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.
Public/Granted literature
- US20140373150A1 SYSTEMS, METHODS, AND MEDIA FOR DETECTING NETWORK ANOMALIES Public/Granted day:2014-12-18
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