Intelligent network intrusion prevention feature collection and classification algorithms
Rapid Internet use growth and applications of diverse military have managed researchers to
develop smart systems to help applications and users achieve the facilities through the …
develop smart systems to help applications and users achieve the facilities through the …
Vertical handover algorithm based on multi-attribute and neural network in heterogeneous integrated network
X Tan, G Chen, H Sun - EURASIP Journal on Wireless Communications …, 2020 - Springer
A novel vertical handover algorithm based on multi-attribute and neural network for
heterogeneous integrated network is proposed in this paper. The whole frame of the …
heterogeneous integrated network is proposed in this paper. The whole frame of the …
Machine learning protocol for secure 5G handovers
The fifth generation (5G) networks are characterized with ultra-dense deployment of base
stations with limited footprint. Consequently, user equipment's handover frequently as they …
stations with limited footprint. Consequently, user equipment's handover frequently as they …
Hybrid approach for network intrusion detection system using random forest classifier and rough set theory for rules generation
One of the most dangerous aspects that the computer world glimpses are threats to security.
It estimated that about 3 billion dollars in cybercrime lost each year. It expected that this …
It estimated that about 3 billion dollars in cybercrime lost each year. It expected that this …
PDIWS: Thermal Imaging Dataset for Person Detection in Intrusion Warning Systems
ND Thuan, HS Hong - 2023 IEEE Statistical Signal …, 2023 - ieeexplore.ieee.org
In this paper, we present a synthetic thermal imaging dataset for Person Detection in
Intrusion Warning Systems (PDIWS). The dataset consists of a training set with 2000 images …
Intrusion Warning Systems (PDIWS). The dataset consists of a training set with 2000 images …
Deep ensemble of classifier for intrusion detection in WSN and improved attack mitigation process
M Chandan, SG Santhi… - … : Practice and Experience, 2024 - Wiley Online Library
Attacks have a significant negative impact on the wireless sensor network's network
operations. They target to weaken the network layer, if they are not completely eradicated …
operations. They target to weaken the network layer, if they are not completely eradicated …
[PDF][PDF] Multiple classification algorithm based on graph convolutional neural network for intrusion detection
F Liu, Z Hu, A Zhang, R Du, D Qin, J Xu - 2021 - scholar.archive.org
In order to improve the recognition performance of intrusion detection, a graph convolutional
neural network for multiple classification intrusion detection is proposed, named as GCNID …
neural network for multiple classification intrusion detection is proposed, named as GCNID …
Vertical Handover Algorithm in OpenAirInterface and Neural Network for 4G and 5G Base Stations
The fifth generation (5G) mobile network has been designed to offer individuals and objects
with nearly ubiquitous, ultra-high bandwidth, and low latency access. In heterogeneous …
with nearly ubiquitous, ultra-high bandwidth, and low latency access. In heterogeneous …
Alarm correlation to improve industrial fault management
Actual alarm systems used in manufacturing applications lacks explanation and indication of
the root causes, which results in a poor decision making. In addition, manufacturing systems …
the root causes, which results in a poor decision making. In addition, manufacturing systems …
Design and Implementation of Intrusion Detection System Based on Neural Network
Z Cai, J Wang, J Zhang, X Chen - … 17–20, 2021, Proceedings, Part II 7, 2021 - Springer
With the continuous emergence of cyber-attacks, traditional intrusion detection methods
become increasingly limited. In the field of network security, new intrusion detection methods …
become increasingly limited. In the field of network security, new intrusion detection methods …