This tutorial implements two variants of the Inventory Matching System described in this paper: prime-match.py implements the classical protocol, while prime-match-semi-honest.py follows the semi-honest protocol.

The principle is as follows: a bank has a list of orders, and a client has another list of orders. Orders are either Sell or Buy, followed by an asset. We want to apply the matching between the orders, without the parties to know what are each other orders.

A simple example is

	Bank Orders:
		Sell  10 of C
		 Buy  47 of A
		Sell  31 of D

	Client Orders:
		Sell  50 of A
		Sell  24 of B
		 Buy  18 of D

The corresponding resolution is

	Bank Orders:
		Sell   0 of C
		 Buy  47 of A
		Sell  18 of D

	Client Orders:
		Sell  47 of A
		Sell  24 of B
		 Buy  18 of D

Executing the classic protocol

We can run our prime-match.py to perform the computations: FHE Simulation is done in the clear to build expected results, while FHE is the real FHE computation. Our execution here was done on an hpc7a machine on AWS, with Concrete FIXME.

$ python prime-match.py


FIXME: run that on hpc7a machine

Executing the semi honest protocol

We have executed the semi-honest protocol, still on an hpc7a machine on AWS, with Concrete FIXME.

$ python prime-match-semi-honest.py

FIXME: run that on hpc7a machine