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A hybrid anomaly detection model using G-LDA
2014
2014 IEEE International Advance Computing Conference (IACC)
Anomaly detection is one of the important challenges of network security associated today. We present a novel hybrid technique called G-LDA to identify the anomalies in network traffic. We propose a hybrid technique integrating Latent Dirichlet Allocation and genetic algorithm namely the G-LDA process. Furthermore, feature selection plays an important role in identifying the subset of attributes for determining the anomaly packets. The proposed method is evaluated by carrying out experiments on
doi:10.1109/iadcc.2014.6779336
fatcat:ybgyddbs7feflbeaj7gmr4tmdi