RT Journal Article
T1 Reaching a Consensus on Access Detection by a Decision System
A1 Santos Peñas, Matilde
A1 Guevara Maldonado, César Byron
A1 López López, María Victoria
A1 Martín, José Antonio
AB Classification techniques based on Artificial Intelligence are computational tools that have been applied to detection of intrusions (IDS) with encouraging results. They are able to solve problems related to information security in an efficient way. The intrusion detection implies the use of huge amount of information. For this reason heuristic methodologies have been proposed. In this paper, decision trees, Naive Bayes, and supervised classifying systems UCS, are combined to improve the performance of a classifier. In order to validate the system, a scenario based on real data of the NSL-KDD99 dataset is used.
YR 2014
FD 2014-12-02
LK https://hdl.handle.net/20.500.14352/34872
UL https://hdl.handle.net/20.500.14352/34872
LA eng
NO Ministry of Higher Education, Science, Technology and Innovation (SENESCYT) of the Government of the Republic of Ecuador
DS Docta Complutense
RD 22 abr 2025