A NEURAL-VISUALIZATION IDS FOR HONEYNET DATA
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F12%3A86084429" target="_blank" >RIV/61989100:27740/12:86084429 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1142/S0129065712500050" target="_blank" >http://dx.doi.org/10.1142/S0129065712500050</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1142/S0129065712500050" target="_blank" >10.1142/S0129065712500050</a>
Alternative languages
Result language
angličtina
Original language name
A NEURAL-VISUALIZATION IDS FOR HONEYNET DATA
Original language description
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 inspectionof 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 co
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Neural Systems
ISSN
0129-0657
e-ISSN
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Volume of the periodical
22
Issue of the periodical within the volume
2
Country of publishing house
SG - SINGAPORE
Number of pages
18
Pages from-to
1-18
UT code for WoS article
000302210200005
EID of the result in the Scopus database
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