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

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.

Provided by: Imperial College London Topic: Security Date Added: May 2007 Format: PDF

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