Learn 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)
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)
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)
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)
Recently, research on effective Acoustic Emission (AE)-based methods for condition monitoring and fault detection has attracted many researchers. Due to the complex properties of acoustic signals, effective features for fault detection cannot be easily extracted from the raw acoustic signals. To extract representative features, signal processing techniques(More)
1 Abstract-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(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)