Web-Based Inference DetectionAuthors: J. Staddon, P. Golle and B. Zimny.
Our tools first extract salient keywords from the private data intended for release. Then, they issue search queries for documents that match subsets of these keywords, within a reference corpus (such as the public Web) that encapsulates as much of relevant public knowledge as possible. Finally, our tools parse the documents returned by the search queries for keywords not present in the original private data. These additional keywords allow us to automatically estimate the likelihood of certain inferences. Potentially dangerous inferences are flagged for manual review.
We call this new technology Web-based inference control. The paper reports on two experiments which demonstrate early successes of this technology. The first experiment shows the use of our tools to automatically estimate the risk that an anonymous document allows for re-identification of its author. The second experiment shows the use of our tools to detect the risk that a document is linked to a sensitive topic. These experiments, while simple, capture the full complexity of inference detection and illustrate the power of our approach.