Sketch-based Access Control: A Multimodal Interface for Translating User Preferences into Intent-Aligned Policies
For end-users who struggle to specify access control policies, SBAC provides a more intuitive, iterative authoring workflow that improves policy completeness and precision.
The authors present Sketch-based Access Control (SBAC), a system that uses sketching and multimodal LLMs to help users iteratively refine access control policies. In a user study with 14 participants, the system helped users surface gaps, resolve ambiguities, and validate policies through concrete scenarios.
Developing simple and expressive access controls -- interfaces to specify policies that define who should have access to resources and under what circumstances -- is a longstanding challenge in usable security. We present Sketch-based Access Control (SBAC), a sketch-based, AI-assisted access control authoring system that combines the expressive power of sketching with the interpretive capabilities of multimodal large language models (MLLMs) to support the interpretation and validation of policy specifications as they are iteratively refined. Through a formative study with 14 participants, we identified three design requirements and developed a human-AI collaborative workflow composed of three stages -- Specify, Analyze, and Test -- enabled by the system's ability to maintain and interpret evolving access control specifications. In a user evaluation with 14 participants grounded in their real-world access control scenarios, we found the system and the workflow helped participants progressively refine initially underspecified preferences into more complete and precise policies -- surfacing gaps they had not anticipated, resolving ambiguities through dialogue, and validating policy behavior through concrete scenarios.