[HTML][HTML] A systematic literature review of methods and datasets for anomaly-based network intrusion detection
As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and
threatening. Network intrusion detection has been widely accepted as an effective method to …
threatening. Network intrusion detection has been widely accepted as an effective method to …
Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A systematic review
N Mishra, S Pandya - IEEE Access, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) technology is prospering and entering every part of our lives, be it
education, home, vehicles, or healthcare. With the increase in the number of connected …
education, home, vehicles, or healthcare. With the increase in the number of connected …
A survey of network-based intrusion detection data sets
Labeled data sets are necessary to train and evaluate anomaly-based network intrusion
detection systems. This work provides a focused literature survey of data sets for network …
detection systems. This work provides a focused literature survey of data sets for network …
Increasing the performance of machine learning-based IDSs on an imbalanced and up-to-date dataset
In recent years, due to the extensive use of the Internet, the number of networked computers
has been increasing in our daily lives. Weaknesses of the servers enable hackers to intrude …
has been increasing in our daily lives. Weaknesses of the servers enable hackers to intrude …
Survey on intrusion detection systems based on machine learning techniques for the protection of critical infrastructure
A Pinto, LC Herrera, Y Donoso, JA Gutierrez - Sensors, 2023 - mdpi.com
Industrial control systems (ICSs), supervisory control and data acquisition (SCADA) systems,
and distributed control systems (DCSs) are fundamental components of critical infrastructure …
and distributed control systems (DCSs) are fundamental components of critical infrastructure …
DDoS attack and detection methods in internet-enabled networks: Concept, research perspectives, and challenges
In recent times, distributed denial of service (DDoS) has been one of the most prevalent
security threats in internet-enabled networks, with many internet of things (IoT) devices …
security threats in internet-enabled networks, with many internet of things (IoT) devices …
Transferability of machine learning models learned from public intrusion detection datasets: the CICIDS2017 case study
Intrusion detection is a primary concern in any modern computer system due to the ever-
growing number of intrusions. Machine learning represents an effective solution to detect …
growing number of intrusions. Machine learning represents an effective solution to detect …
Creation of flow-based data sets for intrusion detection
Publicly available labelled data sets are necessary for evaluating anomaly-based Intrusion
Detection Systems (IDSs). However, existing data sets are often not up-to-date or not yet …
Detection Systems (IDSs). However, existing data sets are often not up-to-date or not yet …
Intrusion detection using payload embeddings
Attacks launched over the Internet often degrade or disrupt the quality of online services.
Various Intrusion Detection Systems (IDSs), with or without prevention capabilities, have …
Various Intrusion Detection Systems (IDSs), with or without prevention capabilities, have …
Attack categorisation for IoT applications in critical infrastructures, a survey
With the ever advancing expansion of the Internet of Things (IoT) into our everyday lives, the
number of attack possibilities increases. Furthermore, with the incorporation of the IoT into …
number of attack possibilities increases. Furthermore, with the incorporation of the IoT into …