篇名 | DATA MINING BASED TECHNIQUE FOR IDS ALERT CLASSIFICATION |
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卷期 | 6:1 |
作者 | Hany Nashat Gabra 、 Ayman M. Bahaa-Eldin 、 Hoda Korashy Mohammed |
頁次 | 119-126 |
關鍵字 | Intrusion Detection 、 Data Mining 、 Frequent Pattern 、 Frequent Itemset |
出刊日期 | 201506 |
DOI | 10.7903/ijecs.1392 |
Intrusion detection systems (IDSs) have become a widely used measure for security systems. The main problem for such systems is the irrelevant alerts. We propose a data mining based method for classification to distinguish serious and irrelevant alerts with a performance of 99.9%, which is better in comparison with the other recent data mining methods that achieved 97%. A ranked alerts list is also created according to the alert’s importance to minimize human interventions.