Accession Number : ADA499600


Title :   Numerical Analysis for Relevant Features in Intrusion Detection (NARFid)


Descriptive Note : Master's thesis


Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH GRADUATE SCHOOL OF ENGINEERING AND MANAGEMENT


Personal Author(s) : Gonzalez, Jose A


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a499600.pdf


Report Date : Mar 2009


Pagination or Media Count : 126


Abstract : This thesis evaluates the usefulness of good feature subsets for the general classification task of identifying cyber attacks and network services. The generality of the selected features elucidates the relevance or irrelevance for the classification task of intrusion detection. Additionally, the work provides an extension to assessing features by inter-class separability(Bhattacharyya Coefficient) for multiple class problems, which intends to select the best-performing features for all of the classes.


Descriptors :   *CYBERTERRORISM , *INTRUSION DETECTION(COMPUTERS) , *NUMERICAL ANALYSIS , ARTIFICIAL INTELLIGENCE , COMPUTER NETWORKS , THESES , ATTACK , ALGORITHMS , CLASSIFICATION


Subject Categories : Computer Systems
      Computer Systems Management and Standards


Distribution Statement : APPROVED FOR PUBLIC RELEASE