Design of Adaptive IDS with Regulated Retraining Approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F12%3A86092939" target="_blank" >RIV/61989100:27740/12:86092939 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-642-35326-0" target="_blank" >http://dx.doi.org/10.1007/978-3-642-35326-0</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-35326-0" target="_blank" >10.1007/978-3-642-35326-0</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Design of Adaptive IDS with Regulated Retraining Approach

Popis výsledku v původním jazyce

Computer networks are becoming more insecure and vulnerable to intrusions and attacks as they are increasingly accessible to users globally. To minimize possibility of intrusions and attacks, various intrusion detection models have been proposed. However, the existing procedures suffer high false alarm, not adequately adaptive, low accuracy and rigid. The detection performance deteriorates when behavior of traffic is changing and new attacks continually emerge. Therefore, the need to update the reference model for any given anomaly-based intrusion detection is necessary to keep up with these changes. Severe changes should be addressed immediately before the performance is compromised. Available updating approaches include dynamic, periodic and regulated. Unfortunately, none considers severity of changes to trigger the updating. This paper proposed an adaptive IDS model using regulated retraining approach based on severity of changes in network traffic. Therefore, retraining can be done

Název v anglickém jazyce

Design of Adaptive IDS with Regulated Retraining Approach

Popis výsledku anglicky

Computer networks are becoming more insecure and vulnerable to intrusions and attacks as they are increasingly accessible to users globally. To minimize possibility of intrusions and attacks, various intrusion detection models have been proposed. However, the existing procedures suffer high false alarm, not adequately adaptive, low accuracy and rigid. The detection performance deteriorates when behavior of traffic is changing and new attacks continually emerge. Therefore, the need to update the reference model for any given anomaly-based intrusion detection is necessary to keep up with these changes. Severe changes should be addressed immediately before the performance is compromised. Available updating approaches include dynamic, periodic and regulated. Unfortunately, none considers severity of changes to trigger the updating. This paper proposed an adaptive IDS model using regulated retraining approach based on severity of changes in network traffic. Therefore, retraining can be done

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název statě ve sborníku

Communications in Computer and Information Science. Volume 322

ISBN

978-3-642-35325-3

ISSN

1865-0929

e-ISSN

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Počet stran výsledku

11

Strana od-do

590-600

Název nakladatele

Springer

Místo vydání

Heidelberg

Místo konání akce

Káhira

Datum konání akce

8. 12. 2012

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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