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I've read on wiki that genetic programming has 'outstanding results' in cyberterrorism prevention.

Further more, this abstract says:

Using machine-coded linear genomes and a homologous crossover operator in genetic programming, promising results were achieved in detecting malicious intrusions.

I've checked the study, but it's still not clear for me.

How exactly was this detection achieved from the technical perspective?

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They treated it as a classification problem. While it's common to use some variety of Neural Nets (NNs) to build classifiers, Genetic Programming (GP) can also be used for this purpose. In contrast to NN classifiers, GP can use a wider range of operations (e.g. if,while,logical statements,arbitrary mathematical functions etc) to perform the classification than weighted arithmetic expressions involving an activation function. Whether or not this is actually of benefit depends on the specific application.

In addition, the abstract implies their algorithm is adaptive (i.e. responds in some fashion to the nature of incoming attacks), which would most easily be achieved by continuing to run the GP program in the background to monitor potential intrusions.

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