Adaptive Multiagent System for Network Traffic Monitoring

J 2009

Adaptive Multiagent System for Network Traffic Monitoring

REHÁK, Martin, Michal PĚCHOUČEK, Martin GRILL, Jan STIBOREK, Karel BARTOŠ et. al.

Basic information

Original name

Adaptive Multiagent System for Network Traffic Monitoring

Name in Czech

Adaptivní multiagentní systém pro sledování síťového provozu

Authors

REHÁK, Martin (203 Czech Republic), Michal PĚCHOUČEK (203 Czech Republic), Martin GRILL (203 Czech Republic), Jan STIBOREK (203 Czech Republic), Karel BARTOŠ (203 Czech Republic) and Pavel ČELEDA (203 Czech Republic, guarantor, belonging to the institution)

Edition

IEEE Intelligent Systems, Los Alamitos, CA, USA, IEEE Computer Society, 2009, 1541-1672

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 3.144

RIV identification code

RIV/00216224:14610/09:00042538

Organization unit

Institute of Computer Science

UT WoS

000266330000006

Keywords in English

network intrusion detection; data mining; multiagent systems; trust

Abstract

ORIG CZ

V originále

An application of agent-based data mining for near-real time detection of attacks against the computer networks and connected hosts is based on processing network traffic statistics provided by high-speed network monitoring cards and using a set of known anomaly-detection techniques to identify the anomalous behavior. The individual anomaly-detection methods have relatively high error rates that make them unfit for most practical deployments. Using the agent-based trust modeling technique, the Camnep system fuses the data provided by anomaly-detection methods and progressively builds a better classification with an acceptable error rate. The system uses agent-based self-adaptation techniques to dynamically align its structure with the changes in network traffic structure and attacks.

In Czech

Adaptivní multiagentní systém pro sledování síťového provozu. Systém je založen na agentech využívájící samoadoptujících technik pro dynamické přizpůsobení struktury na základě změn síťového provozu a útoků.

Links

W911NF-08-1-0250, interní kód MU

Name: CAMNEP2 - Reflective-Cognitive Adaptation for Network Intrusion Detection Systems (Acronym: CAMNEP II)

Investor: U.S. Army RDECOM Acquisition Center, Reflective-Cognitive Adaptation for Network Intrusion Detection Systems

Citovat

REHÁK, Martin, Michal PĚCHOUČEK, Martin GRILL, Jan STIBOREK, Karel BARTOŠ and Pavel ČELEDA. Adaptive Multiagent System for Network Traffic Monitoring. IEEE Intelligent Systems. Los Alamitos, CA, USA: IEEE Computer Society, 2009, vol. 24, No 3, p. 16-25. ISSN 1541-1672.

@article{834578,
   author = {Rehák, Martin and Pěchouček, Michal and Grill, Martin and Stiborek, Jan and Bartoš, Karel and Čeleda, Pavel},
   article_location = {Los Alamitos, CA, USA},
   article_number = {3},
   keywords = {network intrusion detection; data mining; multiagent systems; trust},
   language = {eng},
   issn = {1541-1672},
   journal = {IEEE Intelligent Systems},
   title = {Adaptive Multiagent System for Network Traffic Monitoring},
   url = {http://www2.computer.org/portal/web/csdl/doi/10.1109/MIS.2009.42},
   volume = {24},
   year = {2009}
}

TY  - JOUR
ID  - 834578
AU  - Rehák, Martin - Pěchouček, Michal - Grill, Martin - Stiborek, Jan - Bartoš, Karel - Čeleda, Pavel
PY  - 2009
TI  - Adaptive Multiagent System for Network Traffic Monitoring
JF  - IEEE Intelligent Systems
VL  - 24
IS  - 3
SP  - 16-25
EP  - 16-25
PB  - IEEE Computer Society
SN  - 15411672
KW  - network intrusion detection
KW  - data mining
KW  - multiagent systems
KW  - trust
UR  - http://www2.computer.org/portal/web/csdl/doi/10.1109/MIS.2009.42
N2  - An application of agent-based data mining for near-real time detection of attacks against the computer networks and connected hosts is based on processing network traffic statistics provided by high-speed network monitoring cards and using a set of known anomaly-detection techniques to identify the anomalous behavior. The individual anomaly-detection methods have relatively high error rates that make them unfit for most practical deployments. Using the agent-based trust modeling technique, the Camnep system fuses the data provided by anomaly-detection methods and progressively builds a better classification with an acceptable error rate. The system uses agent-based self-adaptation techniques to dynamically align its structure with the changes in network traffic structure and attacks.
ER  -

REHÁK, Martin, Michal PĚCHOUČEK, Martin GRILL, Jan STIBOREK, Karel BARTOŠ and Pavel ČELEDA. Adaptive Multiagent System for Network Traffic Monitoring. \textit{IEEE Intelligent Systems}. Los Alamitos, CA, USA: IEEE Computer Society, 2009, vol.~24, No~3, p.~16-25. ISSN~1541-1672.

Detailed Information on Publication Record