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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
N-Gram Áõ° ³ªÀÌºê º£À̽º¸¦ ÀÌ¿ëÇÑ Á¤È®ÇÑ Ä§ÀÔ Å½Áö |
¿µ¹®Á¦¸ñ(English Title) |
Accurate Intrusion Detection using n-Gram Augmented Naive Bayes |
ÀúÀÚ(Author) |
°´ë±â
Dae-Ki Kang
|
¿ø¹®¼ö·Ïó(Citation) |
VOL 12 NO. 02 PP. 0285 ~ 0288 (2008. 10) |
Çѱ۳»¿ë (Korean Abstract) |
±â°è ÇнÀÀ» ÀÀ¿ëÇÑ ¸¹Àº ħÀÔ Å½Áö ½Ã½ºÅÛµéÀº n-±×·¥ Á¢±Ù ¹æ¹ýÀ» ÁÖ·Î ¾²°í ÀÖ´Ù. ±×·¯³ª, n-±×·¥ Á¢±Ù ¹æ¹ýÀº ÁÖ¾îÁø ½ÃÄö½º¿¡¼ ȹµæÇÑ n-±×·¥µéÀÌ ¼·Î °ãÄ¡´Â ¹®Á¦µéÀ» °¡Áö°í ÀÖ´Ù. º» ¿¬±¸¿¡¼´Â ÀÌ·¯ÇÑ ¹®Á¦µéÀ» ÇØ°áÇϱâ À§ÇØ, n-±×·¥ Áõ° ³ªÀÌºê º£À̽º (n-gram augmented naive Bayes) ¾Ë°í¸®ÁòÀ» ħÀÔ ½ÃÄö½ºÀÇ ºÐ·ù¿¡ Àû¿ëÇÏ¿´´Ù. Á¦¾ÈµÈ ½Ã½ºÅÛÀÇ ¼º´ÉÀ» Æò°¡Çϱâ À§ÇØ n-±×·¥ Ư¡µéÀ» »ç¿ëÇÏ´Â ÀÏ¹Ý ³ªÀÌºê º£À̽º (naive Bayes) ¾Ë°í¸®Áò°ú ¼Æ÷Æ® º¤ÅÍ ¸Ó½Å (support vector machines) ¾Ë°í¸®Áò°ú º» ¿¬±¸¿¡¼ Á¦¾ÈÇÑ n-±×·¥ Áõ° ³ªÀÌºê º£À̽º ¾Ë°í¸®ÁòÀ» ºñ±³ÇÏ¿´´Ù. ´º ¸ß½ÃÄÚ ´ëÇÐÀÇ º¥Ä¡¸¶Å© µ¥ÀÌÅÍ¿¡ Àû¿ëÇØ º» °á°ú¿¡ µû¸£¸é, n-±×·¥ Áõ° ¹æ¹ýÀÌ, n-±×·¥ÀÌ ³ªÀÌºê º£À̽º¿¡ Á÷Á¢ Àû¿ëµÇ´Â °æ¿ì(¿¹: n-±×·¥ Ư¡À» »ç¿ëÇÏ´Â ÀÏ¹Ý ³ªÀÌºê º£À̽º), »ý±â´Â µ¶¸³¼º °¡Á¤¿¡ ´ëÇÑ À§¹è ¹®Á¦µµ ÇØ°áÇϸé¼, µ¿½Ã¿¡ n-±×·¥ Ư¡À» »ç¿ëÇÏ´Â ÀÏ¹Ý ³ªÀÌºê º£À̽ºº¸´Ù ´õ Á¤È®Çϸç, n-±×·¥ Ư¡À» »ç¿ëÇÏ´Â SVM°ú ÇÊÀûÇÒ¸¸ÇÑ ¼öÁØÀÇ Ä§ÀÔ Å½Áö±â¸¦ »ý¼ºÇØ ³»¾ú´Ù. |
¿µ¹®³»¿ë (English Abstract) |
In many intrusion detection applications, n-gram approach has been widely applied. However, n-gram approach has shown a few problems including double counting of features. To address those problems, we applied n-gram augmented Naive Bayes directly to classify intrusive sequences and compared performance with those of Naive Bayes and Support Vector Machines (SVM) with n-gram features by the experiments on host-based intrusion detection benchmark data sets. Experimental results on the University of New Mexico (UNM) benchmark data sets show that the n-gram augmented method, which solves the problem of independence violation that happens when n-gram features are directly applied to Naive Bayes (i.e. Naive Bayes with n-gram features), yields intrusion detectors with higher accuracy than those from Naive Bayes with n-gram features and shows comparable accuracy to those from SVM with n-gram features. |
Å°¿öµå(Keyword) |
N-±×·¥ ³ªÀÌºê º£À̽º ¾Ë°í¸®Áò
ħÀÔ Å½Áö
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