Performance evaluation of deep learning based network intrusion detection system across multiple balanced and imbalanced datasets

A Meliboev, J Alikhanov, W Kim - Electronics, 2022 - mdpi.com
In the modern era of active network throughput and communication, the study of Intrusion
Detection Systems (IDS) is a crucial role to ensure safe network resources and information …

Addressing the class imbalance problem in network intrusion detection systems using data resampling and deep learning

A Abdelkhalek, M Mashaly - The journal of Supercomputing, 2023 - Springer
Network intrusion detection systems (NIDS) are the most common tool used to detect
malicious attacks on a network. They help prevent the ever-increasing different attacks and …

Hybrid strategy improved sparrow search algorithm in the field of intrusion detection

L Tao, M Xueqiang - IEEE Access, 2023 - ieeexplore.ieee.org
Aiming at the problem that Sparrow Search Algorithm (SSA) may fall into local optima and
have slow convergence speed, a hybrid strategy improved sparrow search algorithm …

Machine learning algorithms for raw and unbalanced intrusion detection data in a multi-class classification problem

M Bacevicius, A Paulauskaite-Taraseviciene - Applied Sciences, 2023 - mdpi.com
Various machine learning algorithms have been applied to network intrusion classification
problems, including both binary and multi-class classifications. Despite the existence of …

[HTML][HTML] Advanced Hybrid Transformer-CNN Deep Learning Model for Effective Intrusion Detection Systems with Class Imbalance Mitigation Using Resampling …

H Kamal, M Mashaly - Future Internet, 2024 - mdpi.com
Network and cloud environments must be fortified against a dynamic array of threats, and
intrusion detection systems (IDSs) are critical tools for identifying and thwarting hostile …

Stacking Enabled Ensemble Learning Based Intrusion Detection Scheme (SELIDS) for IoV

AP Singh, BK Chaurasia, A Tripathi - SN Computer Science, 2024 - Springer
A revolutionary approach for enhancing driving efficiency and safety in intelligent
transportation systems (ITS) is deploying autonomous vehicles. Vehicle-to-everything (V2X) …

WS-AWRE: Intrusion Detection Using Optimized Whale Sine Feature Selection and Artificial Neural Network (ANN) Weighted Random Forest Classifier

OA Aldabash, MF Akay - Applied Sciences, 2024 - mdpi.com
An IDS (Intrusion Detection System) is essential for network security experts, as it allows one
to identify and respond to abnormal traffic present in a network. An IDS can be utilized for …

Deep Attention Learning for Extreme Minority Class Intrusion Detection in Network Traffic

K Ghamya, K Prema, PS Kumar… - 2024 International …, 2024 - ieeexplore.ieee.org
In the expansive realm of the Internet, escalating online traffic corresponds to a surge in
sophisticated network attacks. Intrusion Detection Systems (IDS) are pivotal in identifying …

Deep Security Analysis Model for Smart Grid

T Di, Y Wu, W Li - 2022 IEEE 10th International Conference on …, 2022 - ieeexplore.ieee.org
In the face of smart grid attacks generally have a wide variety of problems, we propose a
deep security analysis model based on ensemble learning and single classification …

FRAUD DETECTION UNDER THE UNBALANCED CLASS BASED ON GRADIENT BOOSTING.

R Alothman, H AliTalib… - … -European Journal of …, 2022 - search.ebscohost.com
Credit fraud modeling is an important topic covered by researchers. Overdue risk
management is a critical business link in providing credit loan services. It directly impacts the …