The Subgraph Isomorphism Problem has many applications, including bioinformatics, computer vision and graph databases. Current state-of-the-art solvers using constraints programming techniques can handle cases with up to 1000 pattern vertices and 10,000 target vertices. Symmetry breaking identifies symmetric states during the search process, and avoids searching both. Symmetry breaking techniques have shown promising results in improving the efficiency of algorithms for similar combinatorial problems; presented here are two strategies for implementing symmetry breaking for the Subgraph Isomorphism Problem. Peer reviewed