STG2P: A two-stage pipeline model for intrusion detection based on improved LightGBM and K-means

Z Zhang, L Wang, G Chen, Z Gu, Z Tian, X Du… - … Modelling Practice and …, 2022 - Elsevier
Network attack behavior is always mixed with a large number of normal communications,
which makes the attack characteristics only account for a very small fraction in the log data …

Semi-supervised machine learning framework for network intrusion detection

J Li, H Zhang, Y Liu, Z Liu - The Journal of Supercomputing, 2022 - Springer
Network intrusion detection plays an important role as tools for managing and identifying
potential threats, which presents various challenges. Redundant features and difficult …

A GAN and Feature Selection‐Based Oversampling Technique for Intrusion Detection

X Liu, T Li, R Zhang, D Wu, Y Liu… - Security and …, 2021 - Wiley Online Library
In recent years, there have been numerous cyber security issues that have caused
considerable damage to the society. The development of efficient and reliable Intrusion …

IDS-attention: an efficient algorithm for intrusion detection systems using attention mechanism

FE Laghrissi, S Douzi, K Douzi, B Hssina - Journal of Big Data, 2021 - Springer
Network attacks are illegal activities on digital resources within an organizational network
with the express intention of compromising systems. A cyber attack can be directed by …

I2DS: Interpretable Intrusion Detection System Using Autoencoder and Additive Tree

W Xu, Y Fan, C Li - Security and Communication Networks, 2021 - Wiley Online Library
Intrusion detection system (IDS), the second security gate behind the firewall, can monitor
the network without affecting the network performance and ensure the system security from …

Ensemble classification for intrusion detection via feature extraction based on deep Learning

M Yousefnezhad, J Hamidzadeh, M Aliannejadi - Soft Computing, 2021 - Springer
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 …

A fast network intrusion detection system using adaptive synthetic oversampling and LightGBM

J Liu, Y Gao, F Hu - Computers & Security, 2021 - Elsevier
Network intrusion detection systems play an important role in protecting the network from
attacks. However, Existing network intrusion data is imbalanced, which makes it difficult to …

A bidirectional LSTM deep learning approach for intrusion detection

Y Imrana, Y Xiang, L Ali, Z Abdul-Rauf - Expert Systems with Applications, 2021 - Elsevier
The rise in computer networks and internet attacks has become alarming for most service
providers. It has triggered the need for the development and implementation of intrusion …

SwiftIDS: Real-time intrusion detection system based on LightGBM and parallel intrusion detection mechanism

D Jin, Y Lu, J Qin, Z Cheng, Z Mao - Computers & Security, 2020 - Elsevier
High-speed networks are becoming common nowadays. Naturally, a challenge that arises is
that the intrusion detection system (IDS) should timely detect attacks in huge volumes of …

An efficient intrusion detection method based on LightGBM and autoencoder

C Tang, N Luktarhan, Y Zhao - Symmetry, 2020 - mdpi.com
Due to the insidious characteristics of network intrusion behaviors, developing an efficient
intrusion detection system is still a big challenge, especially in the era of big data where the …