PCA-based Hotelling's T2 chart with fast minimum covariance determinant (FMCD) estimator and kernel density estimation (KDE) for network intrusion detection
In this work, the combination between the Principal Component Analysis (PCA) and the Hotelling's T2 chart is proposed to solve problems caused by the many highly correlated network traffic features and to reduce the computational time without reducing its accuracy detection. However, a new issu...
Saved in:
Main Authors: | Muhammad Mashuri, Muhammad Mashuri, Muhammad Ahsan, Muhammad Ahsan, Lee, Muhammad Hisyam, Prastyo, Dedy Dwi, Wibawati, Wibawati |
---|---|
Format: | Article |
Published: |
Elsevier Ltd
2021
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/97279/ http://dx.doi.org/10.1016/j.cie.2021.107447 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multivariate control chart based on kernel PCA for monitoring mixed variable and attribute quality characteristics
by: Muhammad Ahsan, Muhammad Ahsan, et al.
Published: (2020) -
Robust adaptive multivariate Hotelling's T2 control chart based on kernel density estimation for intrusion detection system
by: Ahsan, Muhammad, et al.
Published: (2020) -
Residual-based maximum MCUSUM control chart for joint monitoring the mean and variability of multivariate autocorrelated processes
by: Hidayatul Khusna, Hidayatul Khusna, et al.
Published: (2019) -
Multivariate change point estimation in covariance matrix using ANN
by: Firouzi, Alireza, et al.
Published: (2020) -
The performance of robust heteroscedasticity consistent covariance matrix estimator
by: Sani, Muhammad, et al.
Published: (2019)