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
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;
Conference_Titel :
Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9247-3
DOI :
10.1109/GCIS.2010.227
