1. An artificial neural network-based data monitoring system for examining from among a plurality of data values sets of data values comprising given input vectors to a neural network in order to detect those data values which are uncharacteristic of an overall pattern of the plurality of data values, comprising: a previously trained autoassociative data monitoring neural network having a knowledge domain wherein a vector within said knowledge domain which is input to said autoassociative neural network is mapped to itself, resulting in an output vector from said autoassociative neural network which is similar to said input vector, said autoassociative neural network including a plurality of individual interrelated nodes disposed in an input layer, an output layer, and at least one hidden layer, and being implemented in the data space of a computer generated application, a difference determining portion associated with said previously trained autoassociative neural network for determining a difference vector representative of the difference between a given input vector and the resulting output vector of said autoassociative neural network, and a difference evaluation portion for determining if, for a given input vector, said difference vector satisfies predetermined criteria, wherein a difference vector satisfying said predetermined criteria is indicative of whether the given input vector is uncharacteristic of the overall pattern of the plurality of data values.