The Relationship Between Reasoning About Privacy and Default Logics

摘要

There is now an incredible wealth of data about individuals, businesses and organisations. This data is freely available over the Internet to almost anyone willing to pay for it, independently of whether they are identity thieves or credit card scam artists or legitimate users. This has led to a growing need for privacy. In this paper, we first present a simple logical model of privacy. We then show that the problem of privacy may be reduced to that of brave reasoning in default logic theories, thus reducing this important problem to a well understood reasoning paradigm. By leveraging this reduction, we are able to develop an efficient privacy preservation algorithm and a set of complexity results for privacy preservation. Efficient systems based on answer set programming are available to implement our algorithm.