Generalizing data to provide anonymity when disclosing information (abstract)
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With the development of Web 2.0 technologies, online social networks are able to provide open platforms to enable the seamless sharing of profile data to enable public developers to interface and extend the social network services as applications (or APIs). At the same time, these open interfaces pose serious privacy concerns as third party applications are usually given full read access to the user profiles. Current related research has focused on mainly user-to-user interactions in social networks, and seems to ignore the third party applications. In this paper, we present an access control framework to manage the third party to user interactions. Our framework is based on enabling the user to specify the data attributes to be shared with the application and at the same time be able to specify the degree of specificity of the shared attributes. We model applications as finite state machines, and use the required user profile attributes as conditions governing the application execution. We formulate the minimal attribute generalization problem and we propose a solution that maps the problem to the shortest path problem to find the minimum set of attribute generalization required to access the application services.