Secure Error-Tolerant Graph Matching Protocols

We consider a setting where there are two parties, each party holds a private graph and they wish to jointly compute the structural dissimilarity between two graphs without revealing any information about their private input graph. Graph edit distance (GED) is a widely accepted metric for measuring the dissimilarity of graphs. It measures the minimum cost for transforming one graph into the other graph by applying graph edit operations. In this paper we present a framework for securely computing approximated GED and as an example, present a protocol based on threshold additive homomorphic encryption scheme. We develop several new sub-protocols such as private maximum computation and optimal assignment protocols to construct the main protocol. We show that our protocols are secure against semi-honest adversaries. The asymptotic complexity of the protocol is O(n` log∗(`)) where ` is the bit length of ring elements and n is the number of nodes in the graph.