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ISI
2004
Springer
14 years 1 months ago
Discovering Hidden Groups in Communication Networks
We describe models and efficient algorithms for detecting groups (communities) functioning in communication networks which attempt to hide their functionality – hidden groups. O...
Jeffrey Baumes, Mark K. Goldberg, Malik Magdon-Ism...
GECCO
2006
Springer
145views Optimization» more  GECCO 2006»
13 years 11 months ago
Immune anomaly detection enhanced with evolutionary paradigms
The paper presents an approach based on principles of immune systems to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by b...
Marek Ostaszewski, Franciszek Seredynski, Pascal B...
IPPS
2006
IEEE
14 years 1 months ago
A nonself space approach to network anomaly detection
The paper presents an approach for the anomaly detection problem based on principles of immune systems. Flexibility and efficiency of the anomaly detection system are achieved by ...
Marek Ostaszewski, Franciszek Seredynski, Pascal B...
SDM
2010
SIAM
182views Data Mining» more  SDM 2010»
13 years 9 months ago
HCDF: A Hybrid Community Discovery Framework
We introduce a novel Bayesian framework for hybrid community discovery in graphs. Our framework, HCDF (short for Hybrid Community Discovery Framework), can effectively incorporate...
Keith Henderson, Tina Eliassi-Rad, Spiros Papadimi...
ACSAC
1999
IEEE
14 years 7 days ago
An Application of Machine Learning to Network Intrusion Detection
Differentiating anomalous network activity from normal network traffic is difficult and tedious. A human analyst must search through vast amounts of data to find anomalous sequenc...
Chris Sinclair, Lyn Pierce, Sara Matzner