Open Source Software Tools for Anomaly Detection Analysis

Report No. ARL-MR-0869
Authors: Robert F. Erbacher and Robinson Pino
Date/Pages: April 2014; 22 pages
Abstract: 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.
Distribution: Approved for public release
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Last Update / Reviewed: April 1, 2014