Likelihood ratios and recurrent random neural networks in detection of Denial of Service attacks

International Symposium on Performance Evaluation of Computer and Telecommunication Systems 2007, SPECTS'07, Part of the 2007 Summer Simulation Multiconference, SummerSim'07

Volumn , Issue , 2007, Pages 608-615

  Loukas, Georgios ^a   Öke, Gülay ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

Bayesian decision taking; Denial of service; Intrusion detection; Network security; Recurrent random neural networks

Indexed keywords

BAYESIAN DECISION; DENIAL OF SERVICE; DENIAL OF SERVICE ATTACKS; DETECTION RATES; DETECTION TECHNIQUE; FALSE ALARMS; INCOMING TRAFFIC; INPUT FEATURES; INPUT TRAFFIC; INTERNET COMMUNICATION; LIKELIHOOD ESTIMATION; LIKELIHOOD RATIOS; RANDOM NEURAL NETWORK; SECURITY THREATS;

COMPUTER SIMULATION; INTRUSION DETECTION; NETWORK SECURITY; NEURAL NETWORKS; TELECOMMUNICATION SYSTEMS; TRANSMISSION CONTROL PROTOCOL;

COMPUTER CRIME;

EID: 84870227311     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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