Now showing items 1-4 of 4
Network anomaly classification by support vector classifiers ensemble and non-linear projection techniques
(Universidad De La Costa, 2013-09-11)
Network anomaly detection is currently a challenge due to the number of different attacks and the number of potential attackers. Intrusion detection systems aim to detect misuses or network anomalies in order to block ...
Feature selection by multi-objective optimisation: application to network anomaly detection by hierarchical self-organising maps
(Universidad de la Costa, 2014-08-11)
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 contributing to decreasing the ...
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 violations according to a predefined ...
Bayesian Classifiers in Intrusion Detection Systems
(Universidad de la Costa, 2020)
To be able to identify computer attacks, detection systems that are based on faults are not dependent on data base upgrades unlike the ones based on misuse. The first type of systems mentioned generate a knowledge pattern ...