2024-03-29T13:38:39Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/38632022-04-29T12:02:47Zcom_10259_3847com_10259_5086com_10259_2604col_10259_3848
2015-10-01T10:17:28Z
urn:hdl:10259/3863
Neural visualization of network traffic data for intrusion detection
Corchado, Emilio
Herrero Cosío, Álvaro
Neural and exploratory projection techniques
Connectionist unsupervised models
Computer network security
Intrusion detection
Network traffic visualization
This study introduces and describes a novel intrusion detection system (IDS) called MOVCIDS (mobile visualization connectionist IDS). This system applies neural projection architectures to detect anomalous situations taking place in a computer network. By its advanced visualization facilities, the proposed IDS allows providing an overview of the network traffic as well as identifying anomalous situations tackled by computer networks, responding to the challenges presented by volume, dynamics and diversity of the traffic, including novel (0-day) attacks. MOVCIDS provides a novel point of view in the field of IDSs by enabling the most interesting projections (based on the fourth order statistics; the kurtosis index) of a massive traffic dataset to be extracted. These projections are then depicted through a functional and mobile visualization interface, providing visual information of the internal structure of the traffic data. The interface makes MOVCIDS accessible from any mobile device to give more accessibility to network administrators, enabling continuous visualization, monitoring and supervision of computer networks. Additionally, a novel testing technique has been developed to evaluate MOVCIDS and other IDSs employing numerical datasets. To show the performance and validate the proposed IDS, it has been tested in different real domains containing several attacks and anomalous situations. In addition, the importance of the temporal dimension on intrusion detection, and the ability of this IDS to process it, are emphasized in this work
2015-10-01T10:17:28Z
2015-10-01T10:17:28Z
2011-03
info:eu-repo/semantics/article
1568-4946
http://hdl.handle.net/10259/3863
10.1016/j.asoc.2010.07.002
eng
Applied soft computing. 2011, V. 11, n. 2, p. 2042-2056
http://dx.doi.org/10.1016/j.asoc.2010.07.002
info:eu-repo/grantAgreement/MICINN/CIT-020000-2008-2
info:eu-repo/grantAgreement/GE/MAGNO2008-1028-CENIT
info:eu-repo/grantAgreement/JCyL/BU006A08
info:eu-repo/semantics/openAccess
Elsevier