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atomic-uaci

Atomic-UACI: Inference-Time AI Content Provenance & Watermarking

⚠️ Status: Specification Stage (v2.1) — This repository contains the formal technical specification and whitepaper for the UACI Framework. Implementation is in active development. Benchmarks reflect design targets validated at specification stage.


What is UACI?

The UACI Framework™ (Universal AI Content Identification System) is the first framework to atomically bind a cryptographic identifier, invisible multimodal watermark, and encrypted provenance vault during inference — across text, image, audio, video, and code.

Most existing approaches handle provenance after generation — post-hoc manifests, separate watermark specs, or siloed per-media solutions. UACI addresses this at the inference layer, before output is released.


The Problem

Gap Current State
No standardised content identifiers Each platform defines provenance differently
Watermarks stripped post-generation No atomic binding at source
Opaque model pipelines No inference-time auditability
Privacy exposure in provenance metadata Plaintext manifests vulnerable

Five-Module Architecture

┌─────────────────────────────────────────────────┐
│                  UACI Framework                  │
├──────────┬──────────────┬────────────────────────┤
│  UACI    │ StealthResist│      PAIR Router        │
│ Protocol │  Watermark   │  (inference middleware) │
├──────────┴──────────────┴────────────────────────┤
│           OpenVeri Toolkit (verification)        │
├──────────────────────────────────────────────────┤
│              P3 Capsule (encrypted vault)        │
└──────────────────────────────────────────────────┘
Module Function
UACI Protocol Cryptographic globally unique identifier — version, timestamp, model fingerprint, content hash, CRC32
StealthResist™ Invisible multimodal watermark — DCT embedding for images, STFT for audio, token insertion for text
PAIR Router Inference-time middleware — atomic injection of ID, watermark, and encrypted vault in a single pass
OpenVeri™ Toolkit Open verification engine — extract watermark, validate header, decrypt vault, verify HMAC
P3 Capsule Privacy-preserving encrypted container — AES-GCM provenance vault with GDPR erasure path

Key Differentiators

Prior Art Limitation UACI Difference
Google SynthID (US 11,706,256) No encrypted vault; separate per-media specs Unified atomic binding across all modalities
C2PA Spec v2.1 Post-hoc cleartext manifests Inference-time atomic binding
Intel GUID (US 11,514,365) No watermark; post-generation only Full cryptographic + watermark + vault pipeline

Performance Targets (Specification Stage)

Operation Median 95th Percentile Setup
ID Generation 3 ± 0.5 ms 6 ± 1.2 ms Intel i7-1165G7, 16GB RAM
Watermark Embed 42 ± 5 ms 68 ± 8 ms CPU only, COCO 1080p
Verification 55 ± 6 ms 80 ± 10 ms CPU/GPU NVIDIA T4
Throughput (batch 4) 250 req/s 4-core VM

⚠️ Image watermark benchmarks validated at specification stage. Audio and video recovery metrics are roadmap items — see roadmap.


Governance & Compliance Mapping

Module NIST SP 800-53 ISO/IEC 42001 EU AI Act / GDPR
UACI Protocol SC-16, AU-10 A.5, A.8 Art 52 transparency
StealthResist SC-7 A.9
P3 Capsule MP-6, AC-17 A.6 GDPR Art 17 erasure

Repository Structure

atomic-uaci/
├── README.md
├── LICENSE
├── WHITEPAPER.md          — Full technical whitepaper v2.1
├── docs/
│   ├── architecture.md    — Five-module architecture detail
│   ├── security.md        — STRIDE threat model and mitigations
│   ├── compliance.md      — Governance and regulatory mapping
│   ├── benchmarks.md      — Performance specifications
│   └── roadmap.md         — Development roadmap
├── schemas/
│   └── p3-capsule.json    — P3 Capsule provenance schema
└── specs/
    └── uaci-protocol.md   — UACI Protocol field specification

Roadmap

Milestone Target Status
Specification v2.1 Q1 2026 ✅ Complete
POC Implementation Q2 2026 🔄 In progress
Audio/Video Benchmarks Q3 2026 ⏳ Planned
Blockchain Registry Pilot Q4 2026 ⏳ Planned
ISO/IEC 42001 Engagement Q1 2027 ⏳ Planned
C2PA & W3C DID WG Contribution Q1 2027 ⏳ Planned

License

MIT License — see LICENSE


Author

Roshan George Thomas Independent AI Researcher — Bahrain ORCID: 0009-0002-1175-7749 Organisation: XwhyZ-WHYLD

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