TSE-IDS: A two-stage classifier ensemble for intelligent anomaly-based intrusion detection system
Intrusion detection systems (IDSs) play a pivotal role in computer security by discovering
and repealing malicious activities in computer networks. Anomaly-based IDS, in particular …
and repealing malicious activities in computer networks. Anomaly-based IDS, in particular …
Dimensionality reduction with IG-PCA and ensemble classifier for network intrusion detection
Handling redundant and irrelevant features in high-dimension datasets has caused a long-
term challenge for network anomaly detection. Eliminating such features with spectral …
term challenge for network anomaly detection. Eliminating such features with spectral …
Building an intrusion detection system using a filter-based feature selection algorithm
Redundant and irrelevant features in data have caused a long-term problem in network
traffic classification. These features not only slow down the process of classification but also …
traffic classification. These features not only slow down the process of classification but also …
A consolidated decision tree-based intrusion detection system for binary and multiclass imbalanced datasets
The widespread acceptance and increase of the Internet and mobile technologies have
revolutionized our existence. On the other hand, the world is witnessing and suffering due to …
revolutionized our existence. On the other hand, the world is witnessing and suffering due to …
A systematic review of defensive and offensive cybersecurity with machine learning
This is a systematic review of over one hundred research papers about machine learning
methods applied to defensive and offensive cybersecurity. In contrast to previous reviews …
methods applied to defensive and offensive cybersecurity. In contrast to previous reviews …
An efficient intrusion detection system based on hypergraph-Genetic algorithm for parameter optimization and feature selection in support vector machine
Realization of the importance for advanced tool and techniques to secure the network
infrastructure from the security risks has led to the development of many machine learning …
infrastructure from the security risks has led to the development of many machine learning …
An effective intrusion detection framework based on MCLP/SVM optimized by time-varying chaos particle swarm optimization
Many organizations recognize the necessities of utilizing sophisticated tools and systems to
protect their computer networks and reduce the risk of compromising their information …
protect their computer networks and reduce the risk of compromising their information …
PCA filtering and probabilistic SOM for network intrusion detection
The growth of the Internet and, consequently, the number of interconnected computers, has
exposed significant amounts of information to intruders and attackers. Firewalls aim to detect …
exposed significant amounts of information to intruders and attackers. Firewalls aim to detect …
An improved NSGA-III algorithm for feature selection used in intrusion detection
Feature selection can improve classification accuracy and decrease the computational
complexity of classification. Data features in intrusion detection systems (IDS) always …
complexity of classification. Data features in intrusion detection systems (IDS) always …
Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps
Feature selection is an important and active issue in clustering and classification problems.
By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus …
By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus …