In this paper, we execute anomaly detection over the computer networks using various machine learning algorithms. We then combine these algorithms to boost ...

In this paper, we employ three different machine learning algorithms that perform binary classification. We use neural networks, decision trees and logistic ...

A Comprehensive Survey on Ensemble Learning-Based Intrusion Detection Approaches in Computer Networks · Computer Science, Engineering. IEEE Access · 2023.

Ali H. Mirza (2018) [1] used logistic regression, neural networks, and decision trees for intrusion detection and reduced dataset dimensions using PCA. Ensemble ...

In this paper, we execute anomaly detection over the computer networks using various machine learning algorithms. We then combine these algorithms to boost ...

This paper provides a comprehensive analysis of some existing ML classifiers for identifying intrusions in network traffic and proposes an ensemble and ...

Oct 30, 2023 · This research presents a comprehensive Systematic Review of the Literature where works related to intrusion detection with ensemble learning were obtained.

We conducted a comparative analysis of various ensemble models with multiple base classifiers ... Intrusion detection in computer networks by multiple classifier ...

In this paper, we present an intrusion detection model based on Ensemble of classifiers such as AdaBoost, MultiBoosting and Bagging to gain more opportunity of ...

Here, the ensemble model is formed by combining K-means with deep learning classifiers such as Long Short term Memory (LSTM) network,. Convolutional Neural ...