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论文研究 arxiv.org ·

从对齐到访问控制:生成式AI策略执行框架

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arXiv 论文(cs.CR,2026年9月22日提交)探讨生成式AI应用中的策略执行问题。作者指出 GenAI 能力发展迅速而安全与合规机制演进缓慢,已造成真实安全事件,且不同实践者对“策略”理解不一,导致方案割裂、难以满足合规要求。论文提出一套方法论,用于系统化分析和拆解现有策略定义与执行方式,并据此给出建议与社区行动呼吁。该文是作者 USENIX Security 2026 Enigma 演讲“From Alignment to Access Control: A Unified View of GenAI Policy Enforcement”的配套扩展。

AI推荐理由 arXiv 安全方向新论文,作者 Nathalie Baracaldo,是 USENIX Security 2026 Enigma 演讲的配套扩展。摘要指出 GenAI 能力发展快而安全机制滞后并已导致真实事件,提出系统化分析现有策略定义与执行方法的方法论,并给出建议与行动呼吁。属于立场/综述类工作,摘要未给出具体技术方案或实验数据,实际落地价值待正文验证。

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Computer Science > Cryptography and Security arXiv:2609.26682 (cs) [Submitted on 22 Sep 2026] Title:From Alignment to Access Control: A Framework for GenAI Policy Enforcement Authors:Nathalie Baracaldo View a PDF of the paper titled From Alignment to Access Control: A Framework for GenAI Policy Enforcement, by Nathalie Baracaldo View PDF HTML (experimental) Abstract:Generative AI (GenAI) applications have flourished enabling users to chat with large language models, and to create agents to act on their behalf for a variety of tasks. The pace of development of capabilities in this field is incredibly fast with security and safety taking a back seat. Unfortunately, the slower pace at which security and safety mechanisms have evolved has led to real incidents. Policy enables the definition of desirable behavior of applications, and for that reason, it is a cornerstone of making systems secure and compliant. Policy however means different things to different practitioners creating confusion and siloed solutions that are not adequate for compliance. This paper takes a tour of the good, the bad and the ugly when it comes to policy enforcement in GenAI applications. We propose a methodology to systematically analyze and dissect existing approaches to define and enforce policy found in the wild. Based on this principled analysis, we provide recommendations and call for action for the community to address. This paper is a companion extension of USENIX Security 2026 Enigma talk titled "From Alignment to Access Control: A Unified View of GenAI Policy Enforcement" by the author Nathalie Baracaldo. Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) Cite as: arXiv:2609.26682 [cs.CR] (or arXiv:2609.26682v1 [cs.CR] for this version) https://doi.org/10.48550/arXiv.2609.26682 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Nathalie Baracaldo Dr. [view email] [v1] Tue, 22 Sep 2026 16:40:57 UTC (1,733 KB) Full-text links: Access Paper: View a PDF of the paper titled From Alignment to Access Control: A Framework for GenAI Policy Enforcement, by Nathalie Baracaldo View PDF HTML (experimental) TeX Source view license Current browse context: cs.CR new | recent | 2026-09 Change to browse by: cs cs.AI References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)

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