Abstract: Method and system for the detection of anomalous behavior in systems displaying typical and complex behavior encoded in a digital signal through the study of a computational model (artificial system) of interacting agents defined using the information contained in the digital signal and imposing that agents engage in a maximally frustrated dynamics. Changes in the target system's behavior lead a measurable decrease in frustration of the artificial system, from sequences never presented before during the system's normal behavior or combinations of already presented sequences never seen together.