(PDF) Adaptive Intrusion Detection: A Data Mining Approach
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In this paper we describe a data mining framework for constructing intrusion detection models. The first key idea is to mine system audit data for ...
Abstract. In this paper we describe a data mining framework for constructing intrusion detec- tion models. The first key idea is to mine system audit data ...
In this paper we describe a data mining framework for constructingintrusion detection models. The first key idea is to mine system auditdata for consistent.
In this paper we describe a data mining framework for constructing intrusion detection models. The first key idea is to mine system audit data for ...
A data mining framework for constructing intrusion detection models that uses meta-learning as a mechanism to makeintrusion detection models more effective ...
... Another application is Intrusion Detection, which aims to detect online behaviour that compromises the confidentiality of the network. In this case, feature ...
We address technical issues and present an adaptive data mining framework for anomaly detection. We employ a sliding window approach and use only the audit ...
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Weak data dependencies in large databases coupled with poorly written web based applications are a major cause for malicious transactions.
Lee, W., Stolfo, S.J. and Mok, K.W. (2000) Adaptive Intrusion Detection A Data Mining Approach. Artificial Intelligence Review, 14, 533-567.
The paper aims at providing IDS based on self learning technique where the system when comes across an unknown data pattern classifies it as an attack or non ...