Neuronové sítě v systémech pro detekci napadení

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Neural networks in intrusion detection systems

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

Neural networks in intrusion detection systems

Popis výsledku anglicky

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

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2004

Kód důvěrnosti údajů

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

Název periodika

Zemědělská ekonomika

ISSN

0139-570X

e-ISSN

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Svazek periodika

50

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

5

Strana od-do

35-39

Kód UT WoS článku

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EID výsledku v databázi Scopus

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