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Title: System and method for anomaly detection

Abstract

A system and method for detecting one or more anomalies in a plurality of observations is provided. In one illustrative embodiment, the observations are real-time network observations collected from a stream of network traffic. The method includes performing a discrete decomposition of the observations, and introducing derived variables to increase storage and query efficiencies. A mathematical model, such as a conditional independence model, is then generated from the formatted data. The formatted data is also used to construct frequency tables which maintain an accurate count of specific variable occurrence as indicated by the model generation process. The formatted data is then applied to the mathematical model to generate scored data. The scored data is then analyzed to detect anomalies.

Inventors:
Issue Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1176372
Patent Number(s):
7739082
Application Number:
11/423,046
Assignee:
Battelle Memorial Institute (Richland, WA)
Patent Classifications (CPCs):
G - PHYSICS G06 - COMPUTING G06Q - DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES
H - ELECTRICITY H04 - ELECTRIC COMMUNICATION TECHNIQUE H04L - TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Scherrer, Chad. System and method for anomaly detection. United States: N. p., 2010. Web.
Scherrer, Chad. System and method for anomaly detection. United States.
Scherrer, Chad. Tue . "System and method for anomaly detection". United States. https://www.osti.gov/servlets/purl/1176372.
@article{osti_1176372,
title = {System and method for anomaly detection},
author = {Scherrer, Chad},
abstractNote = {A system and method for detecting one or more anomalies in a plurality of observations is provided. In one illustrative embodiment, the observations are real-time network observations collected from a stream of network traffic. The method includes performing a discrete decomposition of the observations, and introducing derived variables to increase storage and query efficiencies. A mathematical model, such as a conditional independence model, is then generated from the formatted data. The formatted data is also used to construct frequency tables which maintain an accurate count of specific variable occurrence as indicated by the model generation process. The formatted data is then applied to the mathematical model to generate scored data. The scored data is then analyzed to detect anomalies.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2010},
month = {6}
}

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