RT info:eu-repo/semantics/article
T1 A neural-visualization IDS for honeynet data
A1 Herrero Cosío, Álvaro
A1 Zurutuza, Urko
A1 Corchado, Emilio
K1 Artificial Neural Networks
K1 Unsupervised Learning
K1 Projection Models
K1 Network & Computer Security
K1 Intrusion Detection
K1 Honeypots
K1 Computer science
K1 Informática
AB 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
PB World Scientific Publishing
SN 0129-0657
YR 2012
FD 2012-04
LK http://hdl.handle.net/10259/3861
UL http://hdl.handle.net/10259/3861
LA eng
NO 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
DS Repositorio Institucional de la Universidad de Burgos
RD 24-dic-2024