Not All Large Language Model Deployments Are Created Equal: A Taxonomy-Driven Survey of Security, Defense, and Governance

Abstract

The rapid enterprise adoption of Large Language Models (LLMs) has generated an expanding attack surface that existing surveys address monolithically, leaving engineering practitioners without deployment-specific guidance. This survey organizes the LLM security and governance landscape along two system design dimensions—user accountability boundary and data exposure temporality—yielding four deployment archetypes: Secured Repository, Managed Pipeline, Fortified Service, and Contested Interface. T

Categories

@misc{kang2026not,
  title = {{Not All Large Language Model Deployments Are Created Equal: A Taxonomy-Driven Survey of Security, Defense, and Governance}},
  author = {Nathaniel Kang and Jongho Im},
  year = {2026},
  doi = {10.2139/ssrn.6837687},
  url = {https://doi.org/10.2139/ssrn.6837687}
}