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

Fuente: arXiv
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Hauptverfasser: Sonune, Pratik, Rai, Ritwik, Sural, Shamik, Atluri, Vijayalakshmi, Kundu, Ashish
Format: Preprint
Veröffentlicht: 2025
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author Sonune, Pratik
Rai, Ritwik
Sural, Shamik
Atluri, Vijayalakshmi
Kundu, Ashish
author_facet Sonune, Pratik
Rai, Ritwik
Sural, Shamik
Atluri, Vijayalakshmi
Kundu, Ashish
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2502_12460
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle LMN: A Tool for Generating Machine Enforceable Policies from Natural Language Access Control Rules using LLMs
Sonune, Pratik
Rai, Ritwik
Sural, Shamik
Atluri, Vijayalakshmi
Kundu, Ashish
Cryptography and Security
Machine Learning
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.
title LMN: A Tool for Generating Machine Enforceable Policies from Natural Language Access Control Rules using LLMs
topic Cryptography and Security
Machine Learning
url https://arxiv.org/abs/2502.12460