2026-04-27T17:49:48Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/38612022-04-29T12:02:47Zcom_10259_3847com_10259_5086com_10259_2604col_10259_3848
Herrero Cosío, Álvaro
283
500
0000-0002-2444-5384
Zurutuza, Urko
5611f994-3a7b-40ef-a14c-7e745281309a
500
Corchado, Emilio
125
500
2015-10-01T09:34:40Z
2015-10-01T09:34:40Z
2012-04
0129-0657
http://hdl.handle.net/10259/3861
10.1142/S0129065712500050
Neural intelligent systems can provide a visualization of the network traffic for security staff, in order to reduce the widely known high false-positive rate associated with misuse-based Intrusion Detection Systems (IDSs). Unlike previous work, this study proposes an unsupervised neural models that generate an intuitive visualization of the captured traffic, rather than network statistics. These snapshots of network events are immensely useful for security personnel that monitor network behavior. The system is based on the use of different neural projection and unsupervised methods for the visual inspection of honeypot data, and may be seen as a complementary network security tool that sheds light on internal data structures through visual inspection of the traffic itself. Furthermore, it is intended to facilitate verification and assessment of Snort performance (a well-known and widely-used misuse-based IDS), through the visualization of attack patterns. Empirical verification and comparison of the proposed projection methods are performed in a real domain, where two different case studies are defined and analyzed
Regional Government of Gipuzkoa, the Department of Research, Education and Universities of the Basque Government, and the Spanish Ministry of Science and Innovation (MICINN) under projects TIN2010-21272-C02-01 and CIT-020000-2009-12 (funded by the European Regional Development Fund). This work was also supported in the framework of the IT4Innovations Centre of Excellence project, reg. no. CZ.1.05/1.1.00/02.0070 supported by the Operational Program 'Research and Development for Innovations' funded through the Structural Funds of the European Union and the state budget of the Czech Republic
Electronic version of an article published as International Journal of Neural Systems, Volume 22, Issue 02, April 2012 10.1142/S0129065712500050 ©copyright World Scientific Publishing Company http://www.worldscientific.com/worldscinet/ijns
application/pdf
eng
World Scientific Publishing
International Journal of Neural Systems. 2012, V. 22, n. 2, 1250005
http://www.worldscientific.com/doi/abs/10.1142/S0129065712500050
info:eu-repo/grantAgreement/MICINN/TIN2010-21272-C02-01
info:eu-repo/grantAgreement/MICINN/CIT-020000-2009-12
info:eu-repo/grantAgreement/MICINN/UE/RDI/CZ.1.05/1.1.00/02.0070
Artificial Neural Networks
Unsupervised Learning
Projection Models
Network & Computer Security
Intrusion Detection
Honeypots
Computer science
Informática
A neural-visualization IDS for honeynet data
info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
info:eu-repo/semantics/openAccess
THUMBNAIL
Herrero-IJNS_2012.pdf.jpg
Herrero-IJNS_2012.pdf.jpg
IM Thumbnail
image/jpeg
3756
https://riubu.ubu.es/bitstream/10259/3861/4/Herrero-IJNS_2012.pdf.jpg
d6e9b21fe8fb4c70d438273f9838d7c9
MD5
4
ORIGINAL
Herrero-IJNS_2012.pdf
Herrero-IJNS_2012.pdf
application/pdf
1950936
https://riubu.ubu.es/bitstream/10259/3861/1/Herrero-IJNS_2012.pdf
92977167bf4e1353ab0dfcccc9b4c824
MD5
1
LICENSE
license.txt
license.txt
text/plain; charset=utf-8
1362
https://riubu.ubu.es/bitstream/10259/3861/2/license.txt
5d013bfa6e473ff0db22cd82a4d71a70
MD5
2
TEXT
Herrero-IJNS_2012.pdf.txt
Herrero-IJNS_2012.pdf.txt
Extracted text
text/plain
69688
https://riubu.ubu.es/bitstream/10259/3861/3/Herrero-IJNS_2012.pdf.txt
cf6d410194d04dcbb8142335e8705a39
MD5
3
10259/3861
oai:riubu.ubu.es:10259/3861
2022-04-29 14:02:47.67
Repositorio Institucional de la Universidad de Burgos
bubrep@ubu.es
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