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A system approach to network modeling for DDoS detection using a Naìve Bayesian classifier
Serugudi V. Raghavan,
Published in
2011
Abstract
Denial of Service(DoS) attacks pose a big threat to any electronic society. DoS and DDoS attacks are catastrophic particularly when applied to highly sensitive targets like Critical Information Infrastructure. While research literature has focussed on using various fundamental classifier models for detecting attacks, the common trend observed in literature is to classify DoS attacks into the broad class of intrusions, which makes proposed solutions to this class of attacks unrealistic in practical terms. In this work, the approach to a carefully engineered, practically realised system to detect DoS attacks using a Naìve Bayesian(NB) classifier is described. The work includes network modeling for two protocols - TCP and UDP. © 2011 IEEE.
About the journal
Journal2011 3rd International Conference on Communication Systems and Networks, COMSNETS 2011
Open AccessNo
Concepts (20)
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    Bayesian
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    Bayesian classifier
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    CLASSIFIER MODELS
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    CRITICAL INFORMATION
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    DDOS ATTACK
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    DDOS DETECTION
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    DENIAL OF SERVICE ATTACKS
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    DETECTING ATTACKS
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    DOS ATTACKS
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    Highly sensitive
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    NETWORK MODELING
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    System approach
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    Bayesian networks
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    Communication systems
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    Computer crime
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    CRITICAL INFRASTRUCTURES
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    Internet protocols
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    Security of data
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    Transmission control protocol
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    Knowledge based systems