• DocumentCode
    2464436
  • Title

    IDS Evaluation Approach Based on MLE-ROC

  • Author

    Liang, Hai-hua ; Chang, Jin-yi ; Li, Ke-qing

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Changshu Inst. of Technol., Changshu, China
  • Volume
    3
  • fYear
    2010
  • fDate
    16-17 Dec. 2010
  • Firstpage
    229
  • Lastpage
    232
  • Abstract
    The measures of Intrusion Detection System (IDS) in special threshold-value are derived from the contingency table. ROC curve facilitates to evaluate general performance of Intrusion Detection System (IDS). In practice, ROC convex hull (ROCCH) method which combines techniques from computational geometry is used, but it maximizes the area under the ROC curve (AUC). In order to maximum likelihood estimation of value of AUC, We propose MLE-ROC, a new algorithm depending on monotonic regression.
  • Keywords
    computational geometry; maximum likelihood estimation; regression analysis; security of data; IDS evaluation approach; MLE-ROC; ROC convex hull method; computational geometry; intrusion detection system; maximum likelihood estimation; monotonic regression; Classification algorithms; Gaussian distribution; Intrusion detection; Machine learning; Machine learning algorithms; Maximum likelihood detection; Maximum likelihood estimation; IDS; MLEROC; ROCCH; contingency table; monotonic regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9247-3
  • Type

    conf

  • DOI
    10.1109/GCIS.2010.227
  • Filename
    5709362