LNNLS‐KH: A Feature Selection Method for Network Intrusion Detection

X Li, P Yi, W Wei, Y Jiang, L Tian - Security and …, 2021 - Wiley Online Library
As an important part of intrusion detection, feature selection plays a significant role in
improving the performance of intrusion detection. Krill herd (KH) algorithm is an efficient …

A Deep Learning‐Based Framework for Feature Extraction and Classification of Intrusion Detection in Networks

M Naveed, F Arif, SM Usman, A Anwar… - Wireless …, 2022 - Wiley Online Library
An intrusion detection system, often known as an IDS, is extremely important for preventing
attacks on a network, violating network policies, and gaining unauthorized access to a …

Intrusion detection methods based on integrated deep learning model

Z Wang, Y Liu, D He, S Chan - computers & security, 2021 - Elsevier
Intrusion detection system can effectively identify abnormal data in complex network
environments, which is an effective method to ensure computer network security. Recently …

[HTML][HTML] Evaluating neural networks using Bi-Directional LSTM for network IDS (intrusion detection systems) in cyber security

TS Pooja, P Shrinivasacharya - Global Transitions Proceedings, 2021 - Elsevier
An Intrusion detection system is a fundamental layer incorporated in the network system.
Due to enormous amount of traffic in the Network, the attacker waits for the chance to cause …

Building an efficient intrusion detection system based on feature selection and ensemble classifier

Y Zhou, G Cheng, S Jiang, M Dai - Computer networks, 2020 - Elsevier
Intrusion detection system (IDS) is one of extensively used techniques in a network topology
to safeguard the integrity and availability of sensitive assets in the protected systems …

ID-RDRL: a deep reinforcement learning-based feature selection intrusion detection model

K Ren, Y Zeng, Z Cao, Y Zhang - Scientific reports, 2022 - nature.com
Network assaults pose significant security concerns to network services; hence, new
technical solutions must be used to enhance the efficacy of intrusion detection systems …

[PDF][PDF] Intrusion detection in the Internet of Things using fusion of GRU-LSTM deep learning model

MS Al-kahtani, Z Mehmood, T Sadad… - … Automation & Soft …, 2023 - researchgate.net
Cybersecurity threats are increasing rapidly as hackers use advanced techniques. As a
result, cybersecurity has now a significant factor in protecting organizational limits. Intrusion …

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 …

χ2-BidLSTM: A Feature Driven Intrusion Detection System Based on χ2 Statistical Model and Bidirectional LSTM

Y Imrana, Y Xiang, L Ali, Z Abdul-Rauf, YC Hu, S Kadry… - Sensors, 2022 - mdpi.com
In a network architecture, an intrusion detection system (IDS) is one of the most commonly
used approaches to secure the integrity and availability of critical assets in protected …

[PDF][PDF] LSTM deep learning method for network intrusion detection system

A Boukhalfa, A Abdellaoui, N Hmina… - International Journal of …, 2020 - core.ac.uk
The security of the network has become a primary concern for organizations. Attackers use
different means to disrupt services, these various attacks push to think of a new way to block …