This paper tackles the problem of usability and security in access control mechanisms. A theoretical solution for this problem is presented using the combination of automatic rule learning and user interaction. The result is the interactive rule learning approach. Interactive rule learning is designed to complete attribute-based access control to generate concise rule sets even by non-expert en...

Traditionally, rule learners have learned deterministic rules from deterministic data, that is, the rules have been expressed as logical statements and also the examples and their classification have been purely logical. We upgrade rule learning to a probabilistic setting, in which both the examples themselves as well as their classification can be probabilistic. The setting is incorporated in ...