NIMS Data Sets
NetMate is employed to generate flows and compute feature values on the above data sets. Data sets are available for researchers in ARFF/CSV format which are ready to be used with Weka.
SBB is a form of genetic programming based learning algorithm which is designed and developed to solve tasks using a co-evolutionary approach.
Tcpreplay is a suite of BSD GPLv3 licensed tools written by Aaron Turner for UNIX (and Win32 under Cygwin) operating systems which gives you the ability to use previously captured traffic to test a variety of network devices.
We use NetMate at NIMS to convert capture files of network traffic into flow statistics. NetMate lets you generate a comma separated value file containing flows from a capture file.
Tranalyzer2 is a lightweight flow generator and packet analyzer application designed for researchers with an emphasis on simplicity, performance, and scalability.
Softflowd is flow-based network traffic analyser capable of Cisco NetFlow data export. Softflowd semi-statefully tracks traffic flows recorded by listening on a network interface or by reading a packet capture file.
Circos is a software package for visualizing data and information. It visualizes data in a circular layout – this makes Circos ideal for exploring relationships between objects or positions.
Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code.
MOA is an open source framework for data stream mining. It includes a collection of machine learning algorithms including classification, regression, clustering, outlier detection, concept drift detection, and recommender systems.