[HTML][HTML] An Advanced Fitness Function Optimization Algorithm for Anomaly Intrusion Detection Using Feature Selection

SS Hong, E Lee, H Kim - Applied Sciences, 2023 - mdpi.com
Cyber-security systems collect information from multiple security sensors to detect network
intrusions and their models. As attacks become more complex and security systems …

[PDF][PDF] Anomaly-based intrusion detection system based on Feature selection and Majority Voting

ME Magdy, AM Matter, S Hussin, D Hassan… - Indones. J. Electr. Eng …, 2023 - academia.edu
Recently, cyberattacks have been more complex than in the past, as a new cyber-attack is
initiated almost every day. Therefore, researchers should develop efficient intrusion …

An efficient anomaly intrusion detection method with feature selection and evolutionary neural network

S Sarvari, NFM Sani, ZM Hanapi, MT Abdullah - IEEE Access, 2020 - ieeexplore.ieee.org
Recently, with the technological and digital revolution, the security of data is very crucial as a
massive amount of data is generated from various networks. Intrusion Detection System …

[PDF][PDF] Performance analysis of different machine learning techniques for anomaly-based intrusion detection

A Sabha, LS Sharma - International Research Journal of …, 2020 - academia.edu
An Intrusion is an activity that compromises the confidentiality or the availability of the
resource. An Intrusion Detection System is a device or the software that monitors the state of …

Review on feature selection algorithms for anomaly-based intrusion detection system

TA Alamiedy, M Anbar, AK Al-Ani, BN Al-Tamimi… - Recent Trends in Data …, 2019 - Springer
As Internet networks expand, the amount of network threats and intrusions increased, the
demand for an efficient and reliable defense system is required to detect network security …

[PDF][PDF] Anomaly based Intrusion Detection System Using Integration of Features Selection Techniques and Random Forest Classifier

A Srinivas, K Sagar - EasyChair Preprint, 2023 - easychair.org
Today's internets are made up of nearly half a million different networks. In any network
connection, identifying the attacks by their types is a difficult task as different attacks may …

Novel framework for an intrusion detection system using multiple feature selection methods based on deep learning

AEM Eljialy, MY Uddin, S Ahmad - Tsinghua Science and …, 2024 - ieeexplore.ieee.org
Intrusion detection systems (IDSs) are deployed to detect anomalies in real time. They
classify a network's incoming traffic as benign or anomalous (attack). An efficient and robust …

Employing feature selection to improve the performance of intrusion detection systems

R Avila, R Khoury, C Pere… - … on Foundations and …, 2021 - Springer
Intrusion detection systems use datasets with various features to detect attacks and protect
computers and network systems from these attacks. However, some of these features are …

Anomaly-Based Intrusion Detection Systems Using Machine Learning.

A Alqahtani, H AlShaher - Journal of Cybersecurity & …, 2024 - search.ebscohost.com
With the increased use of the Internet, unauthorized access has increased, allowing
malicious users to hack networks and carry out malicious activities. One of the essential …

A Novel Ensemble Method for Network-Based Anomaly Intrusion Detection System

AH Al-Shakarchi, NH Al-A'araji… - … Conference on New …, 2022 - Springer
Anomaly intrusion detection technologies are essential for network and computer security as
the threat gets more serious yearly. Ensemble learning techniques are promising machine …