Peyman Kabiri

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With recent advances in network based technology and increased dependability of our every day life on this technology, assuring reliable operation of network based systems is very important. During recent years, number of attacks on networks has dramatically increased and consequently interest in network intrusion detection has increased among the(More)
This paper reports a research work to address the problem of the large number of alerts generated by the detectors in an intrusion detection system. Some of these alerts are redundant and have to be aggregated; others may follow a certain attack pattern that should be correlated. Generally, this operation is referred to as alert correlation. A more detailed(More)
As Mobile Ad-hoc network (MANET) has become a very important technology, research concerning its security problem, especially, in intrusion detection has attracted many researchers. Feature selection methodology plays a central role in the data analysis process. The proposed features are tested in different network operating conditions. PCA is used to(More)
In recent years, an increasing amount of research has been focused on feature selection techniques. These techniques rely on an idea that by selecting the most discriminant features, it may reduce the number of features and increase the recognition. Instead of using a feature selection technique which has been widely used in multi objective evolutionary(More)
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)
Wavelet transform is a well-known signal processing technique which has proven to be a successful technique in Non-Destructive Testing (NDT). Adopting this technique by Acoustic Emission (AE) method could result in better interpretation of data that are used for fault detection. In this study, AE signals emitted from automobile engines in both faulty and(More)
Intrusion detection is a major research problem in network security. Due to the nonlinear nature of the intrusion attempts, unpredictable behavior of the network traffic and the large number of features in the problem space, intrusion detection systems represent a complicated problem area. Choosing effective and key features for intrusion detection is a(More)