Open Source Software Tools for Anomaly Detection Analysis
Final rept. for period ending Sep 2013
ARMY RESEARCH LAB ADELPHI MD COMPUTATIONAL AND INFORMATION SCIENCES DIRECTORATE
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The goal of this report is to perform an analysis of software tools that could be employed to perform basic research and development of Anomaly-Based Intrusion Detection Systems. The software tools reviewed include Environment for Developing KDD-Applications Supported by Index-Structures ELKI, RapidMiner, SHOGUN toolbox Waikato Environment for Knowledge Analysis Weka machine learning, and Scikit-learn. From the analysis, it is recommended to employ the SHOGUN toolbox or Scikit-learn as both tools are written in C and offers an interface for Python. The python language software is currently employed as a research tool within our in-house team of researchers.
- Computer Programming and Software
- Computer Systems Management and Standards