The use of end-to-end data mining methodologies such as CRISP-DM, KDD process, and
SEMMA has grown substantially over the past decade. However, little is known as to how …

In today's digital age, our dependence on IoT (Internet of Things) and IIoT (Industrial IoT)
systems has grown immensely, which facilitates sensitive activities such as banking …

None of the previously proposed Network Intrusion Detection Systems (NIDSs), which are
subject to fuzzy association rules, can meet real-time requirements because they all apply …

An adaptive intrusion detection system that can detect unknown attacks in real-time network
traffic is a major concern. Conventional adaptive intrusion detection systems are …

Intrusion detection system (IDS) plays a critical role in information security because it
provides the last line protection for those protected hosts or networks when intruders elude …

The NetMine framework allows the characterization of traffic data by means of data mining
techniques. NetMine performs generalized association rule extraction to profile …

Understanding the behavior of a network from a large scale traffic dataset is a challenging
problem. Big data frameworks offer scalable algorithms to extract information from raw data …

Network traffic exhibits a high level of variability over short periods of time. This variability
impacts negatively on the accuracy of anomaly-based network intrusion detection systems …

(57) ABSTRACT A system, method, and computer program product are provided for
detecting and measuring changes in network behavior of communication networks utilizing …

The advance in Web technology has lead to more and more applications being deployed
over the Web service (WS) platform. However, the inherent security weaknesses of the WS …