Relevance Features Selection for Intrusion Detection
作者： Adetunmbi Adebayo Olusola , Oladele S Adeola , Oladuni Abosede Daramola , None
DOI: 10.1007/978-1-4614-0373-9_31
关键词:
摘要: The rapid development of business and other transaction systems over the Internet makes computer security a critical issue. In recent times, data mining machine learning have been subjected to extensive research in intrusion detection with emphasis on improving accuracy classifier. But selecting important features from input lead simplification problem, faster more accurate rates. this paper, we presented relevance each feature KDD’99 dataset class. Rough set degree dependency ratio class were employed determine most discriminating for Empirical results show that seven not relevant any
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