发表机构
IBM Research（IBM研究院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种系统分析GenAI应用中策略执行方法的框架，涵盖从对齐到访问控制，旨在解决安全与合规问题，并提供建议与行动呼吁。
AI 中文摘要
生成式人工智能（GenAI）应用蓬勃发展，使用户能够与大语言模型对话，并创建代理代表他们执行各种任务。该领域能力的发展速度极快，而安全与保障却被置于次要地位。不幸的是，安全与保障机制的演进速度较慢，已导致实际事件的发生。策略能够定义应用程序的理想行为，因此它是使系统安全且合规的基石。然而，策略对不同从业者而言含义不同，造成混淆和孤立解决方案，这些方案不足以满足合规要求。本文审视了GenAI应用中策略执行的优点、缺点和丑陋之处。我们提出了一种方法论，系统性地分析和剖析现有在现实世界中定义和执行策略的方法。基于这一原则性分析，我们提出建议并呼吁社区采取行动。本文是作者Nathalie Baracaldo在USENIX Security 2026 Enigma演讲“从对齐到访问控制：GenAI策略执行的统一视角”的配套扩展。
英文摘要
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.
