Due to the frequency of malicious network activities and network policy violations, intrusion
detection systems (IDSs) have emerged as a group of methods that combats the …

Traditionally, a bottleneck preventing the development of more intelligent systems was the
limited amount of data available. Nowadays, the total amount of information is almost …

This paper proposes a novel intrusion detection system (IDS), named RDTIDS, for Internet-of-
Things (IoT) networks. The RDTIDS combines different classifier approaches which are …

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach,
Ensemble Methods: Foundations and Algorithms shows how these accurate methods are …

Several pruning strategies that can be used to reduce the size and increase the accuracy of
bagging ensembles are analyzed. These heuristics select subsets of complementary …

Nowadays, the number of protein sequences being stored in central protein databases from
labs all over the world is constantly increasing. From these proteins only a fraction has been …

Ensembles, as a widely used and effective technique in the machine learning community,
succeed within a key element—“diversity.” The relationship between diversity and …

Network security plays an essential role in secure communication and avoids financial loss
and crippled services due to network intrusions. Intruders generally exploit the flaws of …

Ensemble pruning deals with the reduction of an ensemble of predictive models in order to
improve its efficiency and predictive performance. The last 12 years a large number of …

Abstract Modern Supervisory Control and Data Acquisition (SCADA) systems used by the
electric utility industry to monitor and control electric power generation, transmission and …