A survey on data-driven network intrusion detection
Data-driven network intrusion detection (NID) has a tendency towards minority attack
classes compared to normal traffic. Many datasets are collected in simulated environments …
classes compared to normal traffic. Many datasets are collected in simulated environments …
An effective intrusion detection approach using SVM with naïve Bayes feature embedding
J Gu, S Lu - Computers & Security, 2021 - Elsevier
Network security has become increasingly important in recent decades, while intrusion
detection system plays a critical role in protecting it. Various machine learning techniques …
detection system plays a critical role in protecting it. Various machine learning techniques …
Cyber security intrusion detection for agriculture 4.0: Machine learning-based solutions, datasets, and future directions
In this paper, we review and analyze intrusion detection systems for Agriculture 4.0 cyber
security. Specifically, we present cyber security threats and evaluation metrics used in the …
security. Specifically, we present cyber security threats and evaluation metrics used in the …
Genetic convolutional neural network for intrusion detection systems
Intrusion detection is the identification of unauthorized access of a computer network. This
paper proposes a novel algorithm for a network intrusion detection system (NIDS) using an …
paper proposes a novel algorithm for a network intrusion detection system (NIDS) using an …
Cyber intrusion detection system based on a multiobjective binary bat algorithm for feature selection and enhanced bat algorithm for parameter optimization in neural …
The staggering development of cyber threats has propelled experts, professionals and
specialists in the field of security into the development of more dependable protection …
specialists in the field of security into the development of more dependable protection …
Z-ACM: An approximate calculation method of Z-numbers for large data sets based on kernel density estimation and its application in decision-making
The concept of a Z-number has obtained plenty of interest for its ability to represent
uncertain and partially reliable information. Z-numbers are also widely used in decision …
uncertain and partially reliable information. Z-numbers are also widely used in decision …
A network surveillance approach using machine learning based control charts
Network surveillance, ie, the detection of anomalous behaviour in communications in a
network, has become an important issue in recent years. In this field, techniques of statistical …
network, has become an important issue in recent years. In this field, techniques of statistical …
An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons
One of the most persistent challenges concerning network security is to build a model
capable of detecting intrusions in network systems. The issue has been extensively …
capable of detecting intrusions in network systems. The issue has been extensively …
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 T 2 chart is proposed to solve problems caused by the many highly correlated …
Hotelling's T 2 chart is proposed to solve problems caused by the many highly correlated …
[PDF][PDF] Meticulous elephant herding optimization based protocol for detecting intrusions in cognitive radio ad hoc networks
J Ramkumar, R Vadivel - Int. J. Emerg. Trends Eng. Res, 2020 - researchgate.net
Currently, Identification and detection of intrusions in ad-hoc network is a demanding and
significant task. Numerous methodologies have been proposed for detecting the intrusions …
significant task. Numerous methodologies have been proposed for detecting the intrusions …