Accession Number : ADA599306


Title :   Open Source Software Tools for Anomaly Detection Analysis


Descriptive Note : Final rept. for period ending Sep 2013


Corporate Author : ARMY RESEARCH LAB ADELPHI MD COMPUTATIONAL AND INFORMATION SCIENCES DIRECTORATE


Personal Author(s) : Erbacher, Robert F ; Pino, Robinson


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a599306.pdf


Report Date : Apr 2014


Pagination or Media Count : 22


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.


Descriptors :   *INTRUSION DETECTION(COMPUTERS) , *SOFTWARE TOOLS , ANOMALIES , C PROGRAMMING LANGUAGE , COMPUTER NETWORKS , DATA MINING , LEARNING MACHINES , SURVEYS


Subject Categories : Computer Programming and Software
      Computer Systems Management and Standards


Distribution Statement : APPROVED FOR PUBLIC RELEASE