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» Principled Sampling for Anomaly Detection
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ISSTA
2010
ACM
14 years 13 days ago
Learning from 6, 000 projects: lightweight cross-project anomaly detection
Real production code contains lots of knowledge—on the domain, on the architecture, and on the environment. How can we leverage this knowledge in new projects? Using a novel lig...
Natalie Gruska, Andrzej Wasylkowski, Andreas Zelle...
GECCO
2008
Springer
152views Optimization» more  GECCO 2008»
13 years 9 months ago
Combatting financial fraud: a coevolutionary anomaly detection approach
A major difficulty for anomaly detection lies in discovering boundaries between normal and anomalous behavior, due to the deficiency of abnormal samples in the training phase. In...
Shelly Xiaonan Wu, Wolfgang Banzhaf
RAID
2009
Springer
14 years 3 months ago
Adaptive Anomaly Detection via Self-calibration and Dynamic Updating
The deployment and use of Anomaly Detection (AD) sensors often requires the intervention of a human expert to manually calibrate and optimize their performance. Depending on the si...
Gabriela F. Cretu-Ciocarlie, Angelos Stavrou, Mich...
TMA
2010
Springer
314views Management» more  TMA 2010»
14 years 3 months ago
On the Use of TCP Passive Measurements for Anomaly Detection: A Case Study from an Operational 3G Network
In this work we discuss the use of passive measurements of TCP performance indicators in support of network operation and troubleshooting, presenting a case-study from a real 3G ce...
Peter Romirer-Maierhofer, Angelo Coluccia, Tobias ...
GECCO
2004
Springer
121views Optimization» more  GECCO 2004»
14 years 1 months ago
Network Intrusion Detection Using Genetic Clustering
Abstract. We apply the Unsupervised Niche Clustering (UNC), a genetic niching technique for robust and unsupervised clustering, to the intrusion detection problem. Using the normal...
Elizabeth Leon, Olfa Nasraoui, Jonatan Góme...