Origin Lens: A Privacy-First Mobile Framework for Cryptographic Image Provenance and AI Detection

TL;DR

Origin Lens is a privacy-preserving mobile framework that verifies image provenance and AI-generated content locally on devices, enhancing trust and compliance in visual information.

Contribution

It introduces a novel mobile system combining cryptographic provenance, AI detection, and retrieval verification for on-device visual disinformation assessment.

Findings

Local cryptographic verification on mobile devices

Integration of multiple signals for confidence grading

Alignment with regulatory standards like EU AI Act

Abstract

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.