Dimension reduction using feature extraction methods for real-time misuse detection systems

Gopi K. Kuchimanchi, Vir V. Phoha, Kiran S. Balagani, Shekhar R. Gaddam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

32 Scopus citations

Abstract

We present a novel signed Gain in Information (GI) measure for quantitative evaluation of gain or loss in information due to dimension reduction using feature extraction in misuse detection applications. GI is denned in terms of Sensitivity Mismatch Measure (φ) and Specificity Mismatch Measure (θ). 'φ' quantifies information gain or loss in feature-extracted data as the change in detection accuracy of a misuse detection system when reduced data is used instead of untransformed original data. Similarly, 'θ' quantifies information gain or loss as the change in the number of false alarms generated by a misuse detection system when feature-extracted data is used instead of original data. We present two neural network methods for feature extraction: (1) NNPCA and (2) NLCA for reducing the 41-dimensional KDD Cup 1999 data. We compare our methods with principal component analysis (PCA). Our results show that the NLCA method reduces the test data to approximately 30% of its original size while maintaining a GI comparable to that of PCA and the NNPCA method reduces the test data to approximately 50% with GI measure greater than that of PCA.

Original languageEnglish (US)
Title of host publicationProceedings fron the Fifth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC
Pages195-202
Number of pages8
StatePublished - Dec 1 2004
EventProceedings fron the Fifth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC - West Point, NY, United States
Duration: Jun 10 2004Jun 11 2004

Publication series

NameProceedings fron the Fifth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC

Other

OtherProceedings fron the Fifth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC
CountryUnited States
CityWest Point, NY
Period6/10/046/11/04

Keywords

  • Component analysis
  • Feature selection
  • Network security
  • Real-time misuse intrusion detection
  • Sensitivity mismatch measure
  • Specificity mismatch measure

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Kuchimanchi, G. K., Phoha, V. V., Balagani, K. S., & Gaddam, S. R. (2004). Dimension reduction using feature extraction methods for real-time misuse detection systems. In Proceedings fron the Fifth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC (pp. 195-202). [452] (Proceedings fron the Fifth Annual IEEE System, Man and Cybernetics Information Assurance Workshop, SMC).