A Biologically Inspired Denial of Service Detector Using the Random Neural Network

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Provided by: Imperial College London
Topic: Security
Format: PDF
Several of today's computing challenges have been met by resorting to and adapting optimal solutions that have evolved in nature. For example, autonomic communication networks have started applying biologically-inspired methods to achieve some of their self-properties. The authors build upon such methods to solve the recent problem of detection of denial of service networking attacks, by proposing a combination of bayesian decision making and the Random Neural Networks (RNN) which are inspired by the random spiking behavior of the biological neurons.
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