论文信息 - Performance Analysis of NSL_KDD Data Set Using Neural Networks with Logistic Sigmoid Activation Unit

Performance Analysis of NSL_KDD Data Set Using Neural Networks with Logistic Sigmoid Activation Unit

Network intrusion detection system (NIDS) is a software tool that scans network traffic and performs security analysis on it. NIDS performs match operations upon passing traffic with a pre-established library of attacks in order to identify attacks or abnormal behavior. One of the standard data sets used widely for network intrusion systems is the NSL_KDD data set. The current paper aims to analyze the NSL_KDD data set using artificial neural network with sigmoid activation unit in order to perform a metric analysis study that is aimed at discovering the best fitting parameter values for optimal performance of the given data. Evaluation measures such as accuracy, F-measure, detection rate, and false alarm rate will be used to evaluate the efficiency of the developed model.

Sireesha Rodda | Vignendra Jannela | Shyam Nandan Reddy Uppuluru | Sai Charan Koratala | G. V. S. S. S. Chandra Mouli

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