New techniques for business process matching
Laur Kanger

Two organizations considering possible cooperation may want to check the compatibility of their business processes with each other, and figure out the necessary minimal changes to make them compatible. The business processes may be considered private by the organizations, hence such checks need private computation.

So far, privacy-preserving business process matching has not been considered due to the lack of suitable techniques for privately processing the representations of these processes. In UaESMC, we have recently developed new methods for privacy-preserving processing of graphs, and for random access. Currently, we are working on applying these methods to business processes. In this work, we have to propose a suitable metric on the compatibility of service automata, that is both sensible and amenable to privacy-preserving computation. This metric can be used to compare business processes and privately propose the minimal changes to make them compatible with each other.