用大模型自动解读隐私政策，帮用户看清数据风险
Smart Privacy Policy Assistant: An LLM-Powered System for Transparent and Actionable Privacy Notices
- 用大模型解析隐私条款，分类并打风险标签
- 生成简洁解释，实时提醒敏感信息泄露风险
- 适合普通用户、隐私保护研究者和产品设计者
多数用户在未阅读或理解的情况下同意在线隐私政策，而这些文件决定了个人数据的收集、共享与商业化方式。隐私政策通常冗长、法律术语复杂，非专业人士难以解读。本文提出智能隐私政策助手，一个基于大模型的系统，可自动摄入隐私政策，提取并分类关键条款，赋予可读的风险等级，并生成清晰简洁的解释。该系统通过浏览器插件或移动端界面实现实时应用，在用户披露敏感信息或授予高风险权限前提供上下文警示。我们描述了从政策摄入、条款分类、风险评分到解释生成的端到端流程，并提出了基于条款级准确率、政策级风险一致性及用户理解度的评估框架。
原文摘要 · Abstract (English)
Most users agree to online privacy policies without reading or understanding them, even though these documents govern how personal data is collected, shared, and monetized. Privacy policies are typically long, legally complex, and difficult for non-experts to interpret. This paper presents the Smart Privacy Policy Assistant, an LLM-powered system that automatically ingests privacy policies, extracts and categorizes key clauses, assigns human-interpretable risk levels, and generates clear, concise explanations. The system is designed for real-time use through browser extensions or mobile interfaces, surfacing contextual warnings before users disclose sensitive information or grant risky permissions. We describe the end-to-end pipeline, including policy ingestion, clause categorization, risk scoring, and explanation generation, and propose an evaluation framework based on clause-level accuracy, policy-level risk agreement, and user comprehension.
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