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 …

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 …

Performance analysis of intrusion detection systems using a feature selection method on the UNSW-NB15 dataset

SM Kasongo, Y Sun - Journal of Big Data, 2020 - Springer
Computer networks intrusion detection systems (IDSs) and intrusion prevention systems
(IPSs) are critical aspects that contribute to the success of an organization. Over the past …

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 …

A new intrusion detection system based on using non-linear statistical analysis and features selection techniques

A Al-Bakaa, B Al-Musawi - Computers & Security, 2022 - Elsevier
The increase in the number of connected devices to the Internet and Internet of Things (IoT)
development accompanied a massive increase in the number and types of attacks. Most IoT …

Analysis of Various Supervised Machine Learning Algorithms for Intrusion Detection

K Nagpal, N Jain, A Patra, A Gupta, A Syamala… - … Conference on Cyber …, 2021 - Springer
Computer network intrusion detection systems help recognize unauthorized access and
abnormal attacks over secured networks. It is an important research domain with the advent …

Differentiated Intrusion Detection and SVDD-based Feature Selection for Anomaly Detection

I Kang - 2007 - trace.tennessee.edu
Most of existing intrusion detection techniques treat all types of attacks equally without any
differentiation of the risk they pose to the information system. However, certain types of …

New Wrapper Feature Selection Algorithm for Anomaly-Based Intrusion Detection Systems

M Kherbache, D Espes, K Amroun - … Montreal, QC, Canada, December 1–3 …, 2021 - Springer
With advanced persistent and zero-days threats, the threat landscape is constantly evolving.
Signature-based defense is ineffective against these new attacks. Anomaly-based intrusion …

Machine learning-based intrusion detection: feature selection versus feature extraction

VD Ngo, TC Vuong, T Van Luong, H Tran - Cluster Computing, 2024 - Springer
Abstract Internet of Things (IoTs) has been playing an important role in many sectors, such
as smart cities, smart agriculture, smart healthcare, and smart manufacturing. However, IoT …

Comparative Study of Machine Learning Techniques for Intrusion Detection on CICIDS-2017 Dataset

S Arshad, W Ashraf, S Ashraf, I Hassan… - … on Computing for …, 2023 - ieeexplore.ieee.org
Cyber-attacks are becoming more sophisticated and complicated, making it increasingly
difficult to detect intrusions accurately. Intrusions have the potential to compromise data …