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» Combined Data Mining Approach for Intrusion Detection
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KDD
2008
ACM
195views Data Mining» more  KDD 2008»
14 years 9 months ago
Anomaly pattern detection in categorical datasets
We propose a new method for detecting patterns of anomalies in categorical datasets. We assume that anomalies are generated by some underlying process which affects only a particu...
Kaustav Das, Jeff G. Schneider, Daniel B. Neill
ACSAC
2005
IEEE
14 years 2 months ago
Verify Results of Network Intrusion Alerts Using Lightweight Protocol Analysis
We propose a method to verify the result of attacks detected by signature-based network intrusion detection systems using lightweight protocol analysis. The observation is that ne...
Jingmin Zhou, Adam J. Carlson, Matt Bishop
CIBCB
2008
IEEE
14 years 3 months ago
Temporal and structural analysis of biological networks in combination with microarray data
— We introduce a graph-based relational learning approach using graph-rewriting rules for temporal and structural analysis of biological networks changing over time. The analysis...
Chang Hun You, Lawrence B. Holder, Diane J. Cook
ICDM
2007
IEEE
199views Data Mining» more  ICDM 2007»
14 years 3 months ago
Discovering Structural Anomalies in Graph-Based Data
The ability to mine data represented as a graph has become important in several domains for detecting various structural patterns. One important area of data mining is anomaly det...
William Eberle, Lawrence B. Holder
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 9 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang