Multi-dimensional feature fusion and stacking ensemble mechanism for network intrusion detection
A robust network intrusion detection system (NIDS) plays an important role in cyberspace
security for protecting confidential systems from potential threats. In real world network, there …
security for protecting confidential systems from potential threats. In real world network, there …
Enhancing network intrusion detection using effective stacking of ensemble classifiers with multi-pronged feature selection technique
Information security depends on Network Intrusion Detection (NID), which properly identifies
network threats. This work explores simulating a NID system by stacking ensemble …
network threats. This work explores simulating a NID system by stacking ensemble …
A stacking ensemble for network intrusion detection using heterogeneous datasets
S Rajagopal, PP Kundapur… - Security and …, 2020 - Wiley Online Library
The problem of network intrusion detection poses innumerable challenges to the research
community, industry, and commercial sectors. Moreover, the persistent attacks occurring on …
community, industry, and commercial sectors. Moreover, the persistent attacks occurring on …
Ensemble classification for intrusion detection via feature extraction based on deep Learning
An intrusion detection system is a security system that aims to detect sabotage and
intrusions on networks to inform experts of the attack and abuse of the network. Different …
intrusions on networks to inform experts of the attack and abuse of the network. Different …
Network intrusion detection combined hybrid sampling with deep hierarchical network
K Jiang, W Wang, A Wang, H Wu - IEEE access, 2020 - ieeexplore.ieee.org
Intrusion detection system (IDS) plays an important role in network security by discovering
and preventing malicious activities. Due to the complex and time-varying network …
and preventing malicious activities. Due to the complex and time-varying network …
Dual-IDS: A bagging-based gradient boosting decision tree model for network anomaly intrusion detection system
The mission of an intrusion detection system (IDS) is to monitor network activities and
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
A tree-based stacking ensemble technique with feature selection for network intrusion detection
Several studies have used machine learning algorithms to develop intrusion systems (IDS),
which differentiate anomalous behaviours from the normal activities of network systems. Due …
which differentiate anomalous behaviours from the normal activities of network systems. Due …
A multi-task based deep learning approach for intrusion detection
Q Liu, D Wang, Y Jia, S Luo, C Wang - Knowledge-Based Systems, 2022 - Elsevier
With the frequent occurrence of cyber-security incidents, intrusion detection system (IDS)
has been payed more and more attention recently. However, detecting attacks from traffic …
has been payed more and more attention recently. However, detecting attacks from traffic …
BAT: Deep learning methods on network intrusion detection using NSL-KDD dataset
T Su, H Sun, J Zhu, S Wang, Y Li - IEEE Access, 2020 - ieeexplore.ieee.org
Intrusion detection can identify unknown attacks from network traffics and has been an
effective means of network security. Nowadays, existing methods for network anomaly …
effective means of network security. Nowadays, existing methods for network anomaly …
A supervised machine learning-based solution for efficient network intrusion detection using ensemble learning based on hyperparameter optimization
An efficient machine learning (ML) ensemble technique for categorizing Intrusion Detection
(ID) is proposed in this study. The tuning of the ML model's parameters is a critical topic …
(ID) is proposed in this study. The tuning of the ML model's parameters is a critical topic …