Origin Lens：面向隐私保护的移动框架，用于加密图像溯源与AI检测
Origin Lens: A Privacy-First Mobile Framework for Cryptographic Image Provenance and AI Detection
AI总结：
Origin Lens是一款以隐私为核心、基于移动设备的框架，通过加密图像溯源和AI检测技术，为用户提供本地化的视觉信息验证服务。
摘要：
生成式AI的普及对信息完整性保障提出了挑战，需要能够将模型治理与终端用户验证相连接的系统。我们提出了Origin Lens，这是一个以隐私为核心移动框架，通过分层验证架构针对视觉虚假信息进行检测。与服务器端检测系统不同，Origin Lens通过Rust/Flutter混合架构在设备本地执行加密图像溯源验证和AI检测。我们的系统整合了多种信号，包括加密溯源、生成模型指纹和可选的检索增强验证，为用户提供消费时的分级置信度指标。我们讨论了该框架与监管要求（欧盟AI法案、DSA）的契合度，以及其在补充平台级机制的验证基础设施中的作用。
英文摘要：
The proliferation of generative AI poses challenges for information integrity assurance, requiring systems that connect model governance with end-user verification. We present Origin Lens, a privacy-first mobile framework that targets visual disinformation through a layered verification architecture. Unlike server-side detection systems, Origin Lens performs cryptographic image provenance verification and AI detection locally on the device via a Rust/Flutter hybrid architecture. Our system integrates multiple signals - including cryptographic provenance, generative model fingerprints, and optional retrieval-augmented verification - to provide users with graded confidence indicators at the point of consumption. We discuss the framework's alignment with regulatory requirements (EU AI Act, DSA) and its role in verification infrastructure that complements platform-level mechanisms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
