The continued ability to detect malicious network intrusions has become an exercise in
scalability, in which data mining techniques are playing an increasingly important role. We …

Network intrusion detection systems play an important role in protecting the network from
attacks. However, Existing network intrusion data is imbalanced, which makes it difficult to …

A pattern matching method (signature-based) is widely used in basic network intrusion
detection systems (IDS). A more robust method is to use a machine learning classifier to …

In this paper, a full-regulated neural network (NN) with a double hidden layer recurrent
neural network (DHLRNN) structure is designed, and an adaptive global sliding-mode …

With a plethora of new connections, features, and services introduced, the 5th generation
(5G) wireless technology reflects the development of mobile communication networks and is …

Network attack is a significant security issue for modern society. From small mobile devices
to large cloud platforms, almost all computing products, used in our daily life, are networked …

In this paper, a self-regulated double hidden layer output feedback neural network
(DHLFNN) is presented to control an active power filter (APF) system as a current controller …

Companies seek to promote a swift digitalization of their business processes and new
disruptive features to gain an advantage over their competitors. This often results in a wider …

The Banking sector offers many features to their customers like ATM card, Internet banking,
Gold Loan, Education Loan, Debit card and Credit card for attracting many customers to …

Fraud detection is an enduring topic that pose a threat to banking, insurance, financial
sectors and information security systems such as intrusion detection systems (IDS), etc. Data …