A Vision for Access Control in LLM-based Agent Systems
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arXiv
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| Autores principales: | , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866917026218377216 |
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| author | Li, Xinfeng Huang, Dong Li, Jie Cai, Hongyi Zhou, Zhenhong Dong, Wei Wang, XiaoFeng Liu, Yang |
| author_facet | Li, Xinfeng Huang, Dong Li, Jie Cai, Hongyi Zhou, Zhenhong Dong, Wei Wang, XiaoFeng Liu, Yang |
| contents | The autonomy and contextual complexity of LLM-based agents render traditional access control (AC) mechanisms insufficient. Static, rule-based systems designed for predictable environments are fundamentally ill-equipped to manage the dynamic information flows inherent in agentic interactions. This position paper argues for a paradigm shift from binary access control to a more sophisticated model of information governance, positing that the core challenge is not merely about permission, but about governing the flow of information. We introduce Agent Access Control (AAC), a novel framework that reframes AC as a dynamic, context-aware process of information flow governance. AAC operates on two core modules: (1) multi-dimensional contextual evaluation, which assesses not just identity but also relationships, scenarios, and norms; and (2) adaptive response formulation, which moves beyond simple allow/deny decisions to shape information through redaction, summarization, and paraphrasing. This vision, powered by a dedicated AC reasoning engine, aims to bridge the gap between human-like nuanced judgment and scalable Al safety, proposing a new conceptual lens for future research in trustworthy agent design. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_11108 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Vision for Access Control in LLM-based Agent Systems Li, Xinfeng Huang, Dong Li, Jie Cai, Hongyi Zhou, Zhenhong Dong, Wei Wang, XiaoFeng Liu, Yang Multiagent Systems Artificial Intelligence Cryptography and Security The autonomy and contextual complexity of LLM-based agents render traditional access control (AC) mechanisms insufficient. Static, rule-based systems designed for predictable environments are fundamentally ill-equipped to manage the dynamic information flows inherent in agentic interactions. This position paper argues for a paradigm shift from binary access control to a more sophisticated model of information governance, positing that the core challenge is not merely about permission, but about governing the flow of information. We introduce Agent Access Control (AAC), a novel framework that reframes AC as a dynamic, context-aware process of information flow governance. AAC operates on two core modules: (1) multi-dimensional contextual evaluation, which assesses not just identity but also relationships, scenarios, and norms; and (2) adaptive response formulation, which moves beyond simple allow/deny decisions to shape information through redaction, summarization, and paraphrasing. This vision, powered by a dedicated AC reasoning engine, aims to bridge the gap between human-like nuanced judgment and scalable Al safety, proposing a new conceptual lens for future research in trustworthy agent design. |
| title | A Vision for Access Control in LLM-based Agent Systems |
| topic | Multiagent Systems Artificial Intelligence Cryptography and Security |
| url | https://arxiv.org/abs/2510.11108 |