mlsanityData to 7 Oct 2026

LMN: A Tool for Generating Machine Enforceable Policies from Natural Language Access Control Rules using LLMs

arXiv 2502.12460 ↗First posted 18 Feb 2025cs.CR cs.LGcited by 4

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Abstract (arXiv)

Organizations often lay down rules or guidelines called Natural Language Access Control Policies (NLACPs) for specifying who gets access to which information and when. However, these cannot be directly used in a target access control model like Attribute-based Access Control (ABAC). Manually translating the NLACP rules into Machine Enforceable Security Policies (MESPs) is both time consuming and resource intensive, rendering it infeasible especially for large organizations. Automated machine translation workflows, on the other hand, require information security officers to be adept at using such processes. To effectively address this problem, we have developed a free web-based publicly accessible tool called LMN (LLMs for generating MESPs from NLACPs) that takes an NLACP as input and converts it into a corresponding MESP. Internally, LMN uses the GPT 3.5 API calls and an appropriately chosen prompt. Extensive experiments with different prompts and performance metrics firmly establish the usefulness of LMN.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 2 of its 15 references that are in the map. First posted on arXiv 18 Feb 2025.

Builds on

2 of 15 references.

References · 2

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2014Mining Attribute-Based Access Control Policies from Logscited by 10

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 1.

4 papers.