In this paper, we propose a hybrid intrusion detection algorithm based on Gaussian Mixture Model (GMM) and k-Nearest Neighbors (k-NN). More specifically, we ...
A Hybrid Intrusion Detection Algorithm Based on Gaussian Mixture Model ...
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In this paper, we propose a hybrid intrusion detection algorithm based on. Gaussian Mixture Model (GMM) and k-Nearest Neighbors (k-. NN). More specifically ...
The experimental results indicate that the proposed hybrid intrusion detection algorithm based on Gaussian Mixture Model and k-Nearest Neighbors not only ...
Chun et al. [20] implemented a hybridized system using Gaussian mixture model (GMM) with KNN. GMM has been used to characterize the spatial distribution of each ...
Bibliographic details on A Hybrid Intrusion Detection Algorithm Based on Gaussian Mixture Model and Nearest Neighbors.
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In our technique, we use decision tree for the misuse detection component and Gaussian Mixture Model (GMM) for anomaly detection. The advantage of using GMM is ...
Oct 24, 2020 · Conference Paper. A Hybrid Intrusion Detection Algorithm Based on Gaussian Mixture Model and Nearest Neighbors. October 2019. Chun Long · Yurou ...
This paper proposes an intrusion detection method based on stacked sparse autoencoder and improved Gaussian mixture model (SIGMOD).
Many researchers suggested AIDS system based on single machine learning techniques (SLT) such as K-nearest neighbour (KNN) algorithm [7, 8], Support vector.
Nov 8, 2024 · This study proposes an innovative approach that combines the Adaptive Synthetic (ADASYN) sampling method with a Gaussian Mixture Model (GMM) clustering-based ...