  Finding out the differences and commonalities between the knowledge of two
parties is an important task. Such a comparison becomes necessary, when one
party wants to determine how much it is worth to acquire the knowledge of the
second party, or similarly when two parties try to determine, whether a
collaboration could be beneficial. When these two parties cannot trust each
other (for example, due to them being competitors) performing such a comparison
is challenging as neither of them would be willing to share any of their
assets. This paper addresses this problem for knowledge graphs, without a need
for non-disclosure agreements nor a third party during the protocol.
  During the protocol, the intersection between the two knowledge graphs is
determined in a privacy preserving fashion. This is followed by the computation
of various metrics, which give an indication of the potential gain from
obtaining the other parties knowledge graph, while still keeping the actual
knowledge graph contents secret. The protocol makes use of blind signatures and
(counting) Bloom filters to reduce the amount of leaked information. Finally,
the party who wants to obtain the other's knowledge graph can get a part of
such in a way that neither party is able to know beforehand which parts of the
graph are obtained (i.e., they cannot choose to only get or share the good
parts). After inspection of the quality of this part, the Buyer can decide to
proceed with the transaction.
  The analysis of the protocol indicates that the developed protocol is secure
against malicious participants. Further experimental analysis shows that the
resource consumption scales linear with the number of statements in the
knowledge graph.
