Enhancing Relationship-Based Access Control Policies with Negative Rule Mining

Relationship-based access control (ReBAC) policies often rely solely on positive authorization rules, implicitly denying all other requests by default. However, many scenarios require explicitly stating negative authorization rules to capture exceptions or special restrictions that are not naturally enforced by deny-by-default semantics. This work presents a systematic method to mine ReBAC policies that integrate both positive and negative authorization rules from observed authorizations. We formalize the mining problem, show its NP-hardness, and develop an approach that identifies minimal policies while accurately reflecting observed access decisions. We demonstrate the feasibility and effectiveness of our proposed approach through a set of experiments. Our experimental evaluations on representative datasets demonstrate that including negative rules leads to more concise and semantically complete policies, confirming the necessity of explicit negative authorizations in complex access control settings.