Disinformation techniques for entity resolution

We study the problem of disinformation. We assume that an ``agent'' has some sensitive information that the ``adversary'' is trying to obtain. For example, a camera company (the agent) may secretly be developing its new camera model, and a user (the adversary) may want to know in advance the detailed specs of the model. The agent's goal is to disseminate false information to ``dilute'' what is known by the adversary. We model the adversary as an Entity Resolution (ER) process that pieces together available information. We formalize the problem of finding the disinformation with the highest benefit given a limited budget for creating the disinformation and propose efficient algorithms for solving the problem. We then evaluate our disinformation planning algorithms on real and synthetic data and compare the robustness of existing ER algorithms. In general, our disinformation techniques can be used as a framework for testing ER robustness.