The increasing number of security attacks have inspired researchers to employ various
classifiers, such as support vector machines (SVMs), to deal with them in Intrusion detection …

The increase in hydrocarbon production from problematic production zones having high
fluid loss and formation damage has led to the emergence of non-damaging drilling fluids …

Due to the very fast growth of computer networks, Internet emerges as an important tool to
obtain the desired information. As the data transferred using networks is rapidly increasing …

Nowdays, DNNs (Deep Neural Networks) are widely used in the field of DDoS attack
detection. However, designing a good DNN architecture relies on the designer's experience …

Feature extraction addresses the problem of finding the most compact and informative set of
features. To maximize the effectiveness of each single feature extraction algorithm and to …

The upsurge of drilling in shale and inaccessible reservoirs led to the emergence of Non
Damaging Drilling Fluid (NDDF). Although this drilling fluid is non-invasive, the loss of …

Intrusion Detection System (IDS) is an essential method to protect network security from
incoming on-line threats. Machine learning enable automates the classification of network …

Security is a key issue to both computer and computer networks. Intrusion detection System
(IDS) is one of the major research problems in network security. IDSs are developed to …

Nowadays, detection of various attacks constitutes a significant aspect of network security.
The task of an intrusion detection system (IDS) is to identify and detect any unauthorized …

Nowadays, intelligent learning environments are efficient and interesting solutions for many
complicated problems. Learning automata is an intelligent decision-making scheme that …