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ECBS
2007
IEEE
188views Hardware» more  ECBS 2007»
13 years 9 months ago
Behavior Analysis-Based Learning Framework for Host Level Intrusion Detection
Machine learning has great utility within the context of network intrusion detection systems. In this paper, a behavior analysis-based learning framework for host level network in...
Haiyan Qiao, Jianfeng Peng, Chuan Feng, Jerzy W. R...
KDD
2008
ACM
195views Data Mining» more  KDD 2008»
14 years 7 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
ICNC
2005
Springer
14 years 26 days ago
Applying Genetic Programming to Evolve Learned Rules for Network Anomaly Detection
The DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set is the most widely used public benchmark for testing intrusion detection systems. But the presence...
Chuanhuan Yin, Shengfeng Tian, Houkuan Huang, Jun ...
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...
CORR
2010
Springer
150views Education» more  CORR 2010»
13 years 7 months ago
Dendritic Cells for Real-Time Anomaly Detection
Dendritic Cells (DCs) are innate immune system cells which have the power to activate or suppress the ystem. The behaviour of human DCs is abstracted to form an algorithm suitable...
Julie Greensmith, Uwe Aickelin