The rapid rise in hacking and computer network assaults throughout the world has highlighted need for more effective intrusion detection prevention solutions. system (IDS) is critical identifying abnormalities on network, which have grown size scope. IDS prevents intruders from gaining access to information field of security as a result. use detecting various types attacks. Because traffic data...

The wrapper feature selection approach is useful in identifying informative feature subsets from high-dimensional datasets. Typically, an inductive algorithm “wrapped” in a search algorithm is used to evaluate the merit of the selected features. However, significant bias may be introduced when dealing with highly imbalanced dataset. That is, the selected features may favour one class while bein...

Feature selection for ensembles has shown to be an effective strategy for ensemble creation due to its ability of producing good subsets of features, which make the classifiers of the ensemble disagree on difficult cases. In this paper we present an ensemble feature selection approach based on a hierarchical multi-objective genetic algorithm. The underpinning paradigm is the “overproduce and ch...

The mass of redundant and irrelevant data in network traffic brings serious challenges to intrusion detection, feature selection can effectively remove meaningless information from the data. Most current filtered embedded methods use a fixed threshold or ratio determine number features subset, which requires priori knowledge. In contrast, wrapped are computationally complex time-consuming; mean...

As a system capable of monitoring and evaluating illegitimate network access, an intrusion detection (IDS) profoundly impacts information security research. Since machine learning techniques constitute the backbone IDS, it has been challenging to develop accurate mechanism. This study aims enhance performance IDS by using particle swarm optimization (PSO)-driven feature selection approach hybri...

In cardiology, as in other medical specialties, early and accurate diagnosis of heart disease is crucial it has been the leading cause death over past few decades. Early prediction now more than ever. However, state-of-the-art strategy put emphasis on classifier selection enhancing accuracy performance prediction, seldom considers feature reduction techniques. Furthermore, there are several fac...