| Document Date: 2007-04-30 15:58:30
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City New York / Amsterdam / London / / Company Random Neural Networks / Kindred / Prentice-Hall Inc. / John-Wiley and Sons / / Country Switzerland / United States / United Kingdom / / / Event Force Majeure / / Facility Imperial College / / IndustryTerm driven routing protocol / data mining approach / large networking / victim network / real-time values / neural networks / biophysical neural network / attack tools / e-commerce and online betting websites / artificial neural networks / normal internet traffic / packet networks / energy content / proactive solutions / energy distribution variance / statistical pre-processor / Internet traffic / Web servers / neural network / genetic algorithm / image processing / local reinforcement learning algorithm / real large networking pers / flat energy bursts / detection mechanisms pragmatic solution / change point detection algorithm / energy distribution / signal processing techniques / / OperatingSystem DoS / / Organization Imperial College London / US Federal Reserve / Service of Humans / Comhensive Foundation / / Person Georgios Loukas / Computation / ROC / / Position editor / collector / General / salesman / representative / / Product DoS / / ProvinceOrState Illinois / New York / / PublishedMedium Lecture Notes in Computer Science / / Technology driven routing protocol / CPN routing protocol / local reinforcement learning algorithm / genetic algorithm / statistical pre-processor / machine learning / change point detection algorithm / Quality of Service / image processing / pdf / Neural Network / network routers / data mining / RNNbased networking protocol / simulation / flash / /
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A Denial of Service Detector based on Bayesian Classifiers and the Random Neural Network ¨ ∗ and Georgios Loukas G¨ ulay Oke Electrical and Electronic Engineering, Imperial College London, UK