A novel two-stage deep learning model for network intrusion detection: LSTM-AE

V Hnamte, H Nhung-Nguyen, J Hussain… - Ieee …, 2023 - ieeexplore.ieee.org
Machine learning and deep learning techniques are widely used to evaluate intrusion
detection systems (IDS) capable of rapidly and automatically recognizing and classifying …

Hybrid Detection Technique for IP Packet Header Modifications Associated with Store-and-Forward Operations

A Munshi - Applied Sciences, 2023 - mdpi.com
The detection technique for IP packet header modifications associated with store-and-
forward operation pertains to a methodology or mechanism utilized for the identification and …

A survey of large language models for cyber threat detection

Y Chen, M Cui, D Wang, Y Cao, P Yang, B Jiang… - Computers & …, 2024 - Elsevier
With the increasing complexity of cyber threats and the expanding scope of cyberspace,
there exist progressively more challenges in cyber threat detection. It's proven that most …

[PDF][PDF] Cybersecurity Attack Detection Model, Using Machine Learning Techniques

İ Avcı, M Koca - Acta Polytechnica Hungarica, 2023 - academia.edu
Millions of people use the web every day, in this age of technology and the internet.
Protecting the privacy and security of these users is a significant challenge for cybersecurity …

Fusing multi-source quality statistical data for construction risk assessment and warning based on deep learning

B Gao, Z Ma, J Gu, X Han, P Xiang, X Lv - Knowledge-Based Systems, 2024 - Elsevier
In the context where accidents and fatalities in the construction industry remain persistently
high, the assessment and early warning of construction risks become critically imperative …

Detecting DOS Attacks Using a Hybrid CNN-LSTM Model

M Salehi, A Yari - 2024 10th International Conference on Web …, 2024 - ieeexplore.ieee.org
Given the increasing reliance of critical infrastructure on information and communication
technology, the timely detection and prevention of attacks have become paramount …

HEN: a novel hybrid explainable neural network based framework for robust network intrusion detection

W Wei, S Chen, C Chen, H Wang, J Liu… - Science China …, 2024 - Springer
With the rapid development of network technology and the automation process for 5G, cyber-
attacks have become increasingly complex and threatening. In response to these threats …

Reinforcing Network Security: Network Attack Detection Using Random Grove Blend in Weighted MLP Layers

A Binbusayyis - Mathematics, 2024 - mdpi.com
In the modern world, the evolution of the internet supports the automation of several tasks,
such as communication, education, sports, etc. Conversely, it is prone to several types of …

A Deep Learning Approach for Intrusion Detection Systems in Cloud Computing Environments

WH Aljuaid, SS Alshamrani - Applied Sciences, 2024 - mdpi.com
Cloud computing services have become indispensable to people's lives. Many of their
activities are performed through cloud services, from small companies to large enterprises …

Increasing the resilience of critical infrastructures with defense zone system

A Pallagi, R Peto, E Hronyecz - 2023 IEEE 21st Jubilee …, 2023 - ieeexplore.ieee.org
Protecting critical infrastructure is extremely important, ensuring the continuity and stability of
societal and economic functions. These infrastructures face increasing internal and external …