Pearson correlation attribute evaluation-based feature selection for intrusion detection system

Y Sugianela, T Ahmad - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
IDS helps to overcome the network attack by taking appropriate preventive measures. The
data mining method has good adaptability to new attack types; however, it consumes much …

A hybrid metaheuristic algorithm for features dimensionality reduction in network intrusion detection system

BF Balogun, KA Gbolagade, MO Arowolo… - … Science and Its …, 2021 - Springer
The advent of the Internet computer, and thus the amounts of connected computers in the
last few decades, has opened vast quantities of intelligence to attackers and intruders …

[PDF][PDF] Data Reduction for Optimizing Feature Selection in Modeling Intrusion Detection System.

AN Iman, T Ahmad - International Journal of Intelligent Engineering & …, 2020 - inass.org
With the development and ease of access to internet networks, the potential for attacks and
intrusions have increased. The intrusion detection system (IDS), an approach to overcome …

cFEM: a cluster based feature extraction method for network intrusion detection

MMHU Mazumder, ME Kadir, S Sharmin… - International Journal of …, 2023 - Springer
The recent trend in network intrusion detection leverages key features of machine learning
(ML) algorithms to detect network traffic anomalies. Network traffic flows contain high …

[PDF][PDF] Clustering under-sampling data for improving the performance of intrusion detection system

MN Aziz, T Ahmad - JESTEC, 2021 - jestec.taylors.edu.my
The fast development of information technology has made information security and
computer networks an essential factor. One possible method of protecting these security …

[PDF][PDF] Analyzing ANOVA F-test and Sequential Feature Selection for Intrusion Detection Systems.

MJ Siraj, T Ahmad, RM Ijtihadie - International Journal of Advances in Soft …, 2022 - i-csrs.org
Abstract An Intrusion Detection System (IDS) helps the computer system notify an admin
when an attack is coming to a network. However, some problems may delay this process …

Intrusion Detection System in IoT Network by using Metaheuristic Algorithm with Machine Learning Dimensional Reduction Technique

C Anusha, A Sravani, J Anusha… - … and Networks (ICAN …, 2022 - ieeexplore.ieee.org
The network security is a main problem in any disseminated framework. To providing the
safe and secure network we have been proposed anomaly detection system against from …

RHC: Cluster based Feature Reduction for Network Intrusion Detections

MH Tarek, MMHU Mazumder, S Sharmin… - 2022 IEEE 19th …, 2022 - ieeexplore.ieee.org
Intrusion Detection Systems (IDSs) play an important part in securing computer networks
from different malicious threats and attacks. Modern IDSs leverage machine learning …

[PDF][PDF] PortMap DDoS Attack Detection Using Feature Rank and Machine Learning Algorithms

Y Sugianela, T Ahmad - ICIC Express Letters, Part B …, 2022 - scholar.archive.org
The era of big data, which is coming with a complicated and big scope of data, has caused
the increase of the possibility of network attack. One of those possible attacks is DDoS or …

Data-Driven Techniques for Intrusion Detection in Wireless Networks

LE Alatabani, ES Ali, RA Saeed - Data-Driven Intelligence in …, 2023 - taylorfrancis.com
In a wireless network, there is typically a large amount of data being exchanged over the
network. Having sensitive information about users and network analytics leads to the idea of …