Dynamic SNA-based anomaly detection using unsupervised learning

Details Dynamic SNA-based anomaly detection using unsupervised learning Dynamic SNA-based anomaly detection using unsupervised learning

2006-11-08

2010-06-15

Vincent, David R (Department: 2129)

Data processing: artificial intelligence

Knowledge processing system

C726S023000

Reexamination Certificate

active

07739211

ABSTRACT:
A method, system, and computer program product for enabling dynamic detection of anomalies occurring within an input graph representing a social network. More specifically, the invention provides an automated computer simulation technique that implements the combination of Social Network Analysis (SNA) and statistical pattern classification for detecting abnormal social patterns or events through the expanded use of SNA Metrics. The simulation technique further updates the result sets generated, based on observed occurrences, to dynamically determine what constitutes abnormal behavior, within the overall context of observed patterns of behavior.

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Holzer et al., Email Alias Detection Using Social Network Analysis, Aug. 2005, ACM LinkKDD, pp. 52-57.
Coffman, et al., Mining Graph Data, Dec. 2006, John Wiley & Sons, Chapter 17, pp. 443-469.

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