Real-time risk detection method and protection strategy for intelligent ship network security based on cloud computing

J Guo, H Guo - Symmetry, 2023 - mdpi.com
When studying an unfamiliar system, we first look for the symmetry that the system has, so
that we can make many predictions about the possible properties of the system. The …

SAR-BSO meta-heuristic hybridization for feature selection and classification using DBNover stream data

DK Talapula, KK Ravulakollu, M Kumar… - Artificial Intelligence …, 2023 - Springer
Advancements in cloud technologies have increased the infrastructural needs of data
centers due to storage needs and processing of extensive dimensional data. Many service …

A local feature engineering strategy to improve network anomaly detection

S Carta, AS Podda, DR Recupero, R Saia - Future Internet, 2020 - mdpi.com
The dramatic increase in devices and services that has characterized modern societies in
recent decades, boosted by the exponential growth of ever faster network connections and …

[PDF][PDF] A Global Intrusion Detection System using PcapSockS Sniffer and Multilayer Perceptron Classifier.

A Guezzaz, A Asimi, Y Asimi, Z Tbatou, Y Sadqi - Int. J. Netw. Secur., 2019 - academia.edu
The evolution of networks requires a high monitoring of their resources and a reliable
security of exchanges to obtain a faithful communication between their systems. The …

Heterogeneous Ensemble Feature Selection for Network Intrusion Detection System

YG Damtew, H Chen, Z Yuan - International Journal of Computational …, 2023 - Springer
Intrusion detection systems get more attention to secure the computers and network
systems. Researchers propose different network intrusion detection systems using machine …

[PDF][PDF] An improved CNN approach for network intrusion detection system

J Hu, C Liu, Y Cui - International Journal of Network Security, 2021 - ijns.jalaxy.com.tw
To solve the low average recognition rate of a multiclass intrusion detection system based
on Convolutional Neural Network (CNN), a CNN-based intrusion detection method …

LAN intrusion detection using convolutional neural networks

H Zainel, C Koçak - Applied sciences, 2022 - mdpi.com
The world's reliance the use of the internet is growing constantly, and data are considered
the most precious parameter nowadays. It is critical to keep information secure from …

[PDF][PDF] Exploiting incremental classifiers for the training of an adaptive intrusion detection model.

MR Mohamed, AA Nasr, IF Tarrad… - Int. J. Netw …, 2019 - academia.edu
Due to the fact that network data is dynamic in nature, the demand for adaptive Intrusion
Detection System (IDS) has increased for smart analysis of network data stream. An …

Smmo-cofs: synthetic multi-minority oversampling with collaborative feature selection for network intrusion detection system

YG Damtew, H Chen - International Journal of Computational Intelligence …, 2023 - Springer
Researchers publish various studies to improve the performance of network intrusion
detection systems. However, there is still a high false alarm rate and missing intrusions due …

Optimized common features selection and deep-autoencoder (OCFSDA) for lightweight intrusion detection in Internet of things

U Otokwala, A Petrovski, H Kalutarage - International Journal of …, 2024 - Springer
Embedded systems, including the Internet of things (IoT), play a crucial role in the
functioning of critical infrastructure. However, these devices face significant challenges such …