| 摘要 |
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. It works as a non-parametric statistical test, that is capable of detecting deviations from an arbitrary distribution containing spatial correlations (i.e., correlations between sequences present in the signal) and dynamical correlations (which can evolve in time). The detection system can be applied to intrusion detection in computer security, to the analysis of signals in genomics, proteomics, spectroscopy, imaging, medicine and economy. |
