Gholam Reza Zargar

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Existing intrusion detection techniques emphasize on building intrusion detection model based on all features provided. In feature-based intrusion detection, some selected features may found to be redundant and useless. Feature selection can reduce the computation power requirements and model complexity. This paper proposes a category-based selection of(More)
Existing intrusion detection techniques emphasize on building intrusion detection model based on all features provided. But not all the features are relevant ones and some of them are redundant and useless. This paper proposes and investigates identification of effective network features for Probing attack detection using PCA method to determine an optimal(More)
Existing Intrusion Detection Systems (IDS) examine all the network features to detect intrusion or misuse patterns. In feature-based intrusion detection, some selected features may found to be redundant, useless or less important than the rest. This paper proposes a category-based selection of effective parameters for intrusion detection using Principal(More)
Existing intrusion detection techniques emphasize on building intrusion detection model based on all features provided. But not all the features are relevant ones and some of them are redundant and useless. This paper proposes and investigates identification of effective network features for Probing attack detection using PCA method to determine an optimal(More)
A network data set may contain a huge amount of data and processing this huge amount of data is one of the most challenges task for network based intrusion detection system (IDS). Normally these data contain lots of redundant and irrelevant features. Feature selection approaches are used to extract the relevant features from the original data to improve the(More)
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