Deep learning-based network intrusion detection using multiple image transformers
T Kim, W Pak - Applied Sciences, 2023 - mdpi.com
The development of computer vision-based deep learning models for accurate two-
dimensional (2D) image classification has enabled us to surpass existing machine learning …
dimensional (2D) image classification has enabled us to surpass existing machine learning …
A novel deep hierarchical machine learning approach for identification of known and unknown multiple security attacks in a d2d communications network
Intrusion Detection Systems (IDSs) have played a crucial role in identifying cyber threats for
a very long time. Still, their significance has increased significantly with the advent of 5G/6G …
a very long time. Still, their significance has increased significantly with the advent of 5G/6G …
Network Intrusion Detection using Deep Convolution Neural Network
In recent years, with the rise of cyber attacks, intrusion detection systems (IDS) have become
an essential component of network security. Deep learning-based approaches have shown …
an essential component of network security. Deep learning-based approaches have shown …
A transfer learning-based intrusion detection system for zero-day attack in communication-based train control system
Communication-based train control (CBTC) system is a typical cyber-physical system with
open wireless communication that is vulnerable to attacks. To protect the security of wireless …
open wireless communication that is vulnerable to attacks. To protect the security of wireless …
Explainable artificial intelligence, the fourth pillar of zero trust security
The adoption of zero trust security in today's borderless networks is gaining ground to
combat lateral movement. With a full-scale zero trust security system, malicious actors are …
combat lateral movement. With a full-scale zero trust security system, malicious actors are …
Network Intrusion Detection and Deep Learning Mechanisms
S Chatterjee - 2023 - search.proquest.com
Cyber attack is a strong threat to the digital world. So, it's very essential to keep the network
safe. Network Intrusion Detection system is the system to address this problem. Network …
safe. Network Intrusion Detection system is the system to address this problem. Network …
Root Cause Analysis of Communication Network Based on Deep Fuzzy Neural Network
B Zhang - IEEE Access, 2023 - ieeexplore.ieee.org
In the realm of communication networks, root cause analysis plays a vital role in maintaining
efficient and reliable operation. However, existing root cause analysis methods face …
efficient and reliable operation. However, existing root cause analysis methods face …
Artificial Neural Network Technique for DDOS Attack Prediction in Cyber-IOT System
M Asad, RK Tiwari - 2023 3rd International Conference on …, 2023 - ieeexplore.ieee.org
An intrusion-detection IoT framework is designed to analyze unauthorized access or security
breaches in IoT networks. These systems typically use a combination of hardware and …
breaches in IoT networks. These systems typically use a combination of hardware and …
Optimizing deep neural network using enhanced artificial bee colony algorithm for an efficient intrusion detection system
Owing to ongoing rapid developments in network related technologies combined with the
great surge in their usage, the methodologies for cyber-attacks like intrusions are also …
great surge in their usage, the methodologies for cyber-attacks like intrusions are also …
Coordinated Attacks Detection Simulation With Deep Neural Network Algorithm and Federated Learning
RF Istiqomah, P Sukarno… - 2024 7th World …, 2024 - ieeexplore.ieee.org
This research is focused on comparing the performance of Deep Neural Network (DNN) in
Centralized Learning (CL) and Federated Learning (FL) concepts on simulating coordinated …
Centralized Learning (CL) and Federated Learning (FL) concepts on simulating coordinated …