Event processing is a vital aspect of modern information systems, but is poorly supported and homogenous in nature. The present disclosure recognizes that any detector speaks a language of events. This language of events can be translated into a “Universal Language” such that events from multiple arbitrary detectors may be compared together. The present disclosure uses regular expressions to explore possible relations and patterns across events and across time. The present disclosure further describes a hierarchical architecture such that the events from peer detectors are aggregated and collated and only conglomerate events, those events matching inter- or intra-detector behaviors, are propagated upstream in the hierarchy. Ultimately, this architecture offers a means to merge the event data from an arbitrary number of heterogeneous detectors into a meaningful stream of events that reflect wider breadth of knowledge, improved scalability, and provide a wider context for expression of patterns through the use of regular expressions.