Neural networks in intrusion detection systems

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F04%3A5038" target="_blank" >RIV/60460709:41110/04:5038 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Neural networks in intrusion detection systems

Original language description

Security of an information system is its very important property, especially today, when computers are interconnected via internet. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. For this purposeIntrusion Detection Systems (IDS) were designed. There are two basic models of IDS: misuse IDS and anomaly IDS. Misuse systems detect intrusions by looking for activity that corresponds to known signatures of intrusions or vulnerabilities. Anomaly systems detect intrusions by searching abnormal system activity. Most IDS commercial tools are misuse systems with rule-based expert system structure. However these techniques are less successful when attack characteristics vary from built in signatures. Artificial neural networks offer the potential to resolve these problems. As far as anomaly systems are concerned, it is very difficult to build them, because it is difficult to define normal and abnormal behaviour of a system. Also for build

Czech name

Neuronové sítě v systémech pro detekci napadení

Czech description

Security of an information system is its very important property, especially today, when computers are interconnected via internet. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. For this purposeIntrusion Detection Systems (IDS) were designed. There are two basic models of IDS: misuse IDS and anomaly IDS. Misuse systems detect intrusions by looking for activity that corresponds to known signatures of intrusions or vulnerabilities. Anomaly systems detect intrusions by searching abnormal system activity. Most IDS commercial tools are misuse systems with rule-based expert system structure. However these techniques are less successful when attack characteristics vary from built in signatures. Artificial neural networks offer the potential to resolve these problems. As far as anomaly systems are concerned, it is very difficult to build them, because it is difficult to define normal and abnormal behaviour of a system. Also for build

Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2004

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Zemědělská ekonomika

ISSN

0139-570X

e-ISSN

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Volume of the periodical

50

Issue of the periodical within the volume

1

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

5

Pages from-to

35-39

UT code for WoS article

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EID of the result in the Scopus database

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