  In every enterprise database, administrators must define an access control
policy that specifies which users have access to which assets. Access control
straddles two worlds: policy (organization-level principles that define who
should have access) and process (database-level primitives that actually
implement the policy). Assessing and enforcing process compliance with a policy
is a manual and ad-hoc task. This paper introduces a new paradigm for access
control called Intent-Based Access Control for Databases (IBAC-DB). In IBAC-DB,
access control policies are expressed more precisely using a novel format, the
natural language access control matrix (NLACM). Database access control
primitives are synthesized automatically from these NLACMs. These primitives
can be used to generate new DB configurations and/or evaluate existing ones.
This paper presents a reference architecture for an IBAC-DB interface, an
initial implementation for PostgreSQL (which we call LLM4AC), and initial
benchmarks that evaluate the accuracy and scope of such a system. We further
describe how to extend LLM4AC to handle other types of database deployment
requirements, including temporal constraints and role hierarchies. We propose
RHieSys, a requirement-specific method of extending LLM4AC, and DePLOI, a
generalized method of extending LLM4AC. We find that our chosen implementation,
LLM4AC, vastly outperforms other baselines, achieving high accuracies and F1
scores on our initial Dr. Spider benchmark. On all systems, we find overall
high performance on expanded benchmarks, which include state-of-the-art NL2SQL
data requiring external knowledge, and real-world role hierarchies from the
Amazon Access dataset.
