Models and Algorithms for Graph Watermarking

David Eppstein, Michael T. Goodrich, Jenny Lam, Nil Mamano, Michael Mitzenmacher, Manuel R. Torres

Abstract: We introduce models and algorithmic foundations for graph watermarking. Our approach is based on characterizing the feasibility of graph watermarking in terms of keygen, marking, and identification functions defined over graph families with known distributions. We demonstrate the strength of this approach with exemplary watermarking schemes for two random graph models, the classic Erdős-Rényi model and a random power-law graph model, both of which are used to model real-world networks.