[HTML][HTML] A survey of network intrusion detection systems based on deep learning approaches

DW Al-Safaar, WL Al-Yaseen - Научно-технический вестник …, 2023 - cyberleninka.ru
Currently, most IT organizations are inclined towards a cloud computing environment
because of its distributed and scalable nature. However, its flexible and open architecture is …

[HTML][HTML] A two-tiered framework for anomaly classification in IoT networks utilizing CNN-BiLSTM model

Y Guan, M Noferesti, N Ezzati-Jivan - Software Impacts, 2024 - Elsevier
The paper introduces ACS-IoT, an Anomaly Classification System for IoT networks,
structured as a two-tiered framework. In the first, it employs a decision tree classifier for …

A Review of Intrusion Detection Research Based on Deep Learning

M Deng, Y Kan, H Xu, C Sun - … of the 2nd International Conference on …, 2023 - dl.acm.org
In recent years, the network security situation has become critical. A key component of
network security is intrusion detection. With the continuous development of deep learning …

[PDF][PDF] Hyper-Parameters Consequence on the Performance of Deep Learning Algorithm for Intrusion Detection System

HQ Gheni, WL Al-Yaseen - Journal of University of Babylon for Pure and …, 2024 - iasj.net
Background: The increasing reliance on Internet-based applications has led to a rise in the
number of hackers, posing a significant threat to the security and confidentiality of digital …

A Study on Self-Configuring Intrusion Detection Model based on Hybridized Deep Learning Models

SA Bajpai, AB Patankar - 2023 7th International Conference on …, 2023 - ieeexplore.ieee.org
In order to achieve the necessary security guarantee, Intrusion Detection Systems (IDSs)
play a vital role in all networks and information systems worldwide. One of the best ways to …

ACS-IoT: A CNN-BiLSTM Model for Anomaly Classification in IoT Networks

Y Guan - 2023 - dr.library.brocku.ca
This work proposes an Anomaly Classification System for IoT (ACS-IoT). The proposed
system contains a pipeline of machine learning and deep learning algorithms for the …