Distributed information systems emerged as solution for the needs of enterprises that share information via on-demand access. Information Brokering Systems (IBSs) came into existence to leverage usefulness of sharing information among organizations. The IBS is responsible to integrate loosely coupled systems forming a brokering overlay. The existing IBSs believe that the brokers are trusted and data can be shared through them confidently. However, adversaries can infer information from the metadata available. This is the problem to be addressed. Recently Li et al. proposed an approach for privacy preserving information brokering. They focused two kinds of privacy attacks namely inference attack and attribute-correlation attack. They also proposed two solutions for preventing these attacks. They are query segment encryption and automaton segmentation respectively. With insignificant overhead, their approach provides system-wide security. In this paper, we implemented privacy preserving on-demand access to distributed information brokering system. We built a prototype application that demonstrates the proof of concept.