Trust Identity Protocol (TIP) Whitepaper v5.0
The canonical 140-page specification for the Trust Identity Protocol, the open, post-quantum, federated standard for verified human identity and content provenance on the internet.
Citation
Mendhe, Dinesh. Trust Identity Protocol (TIP) v5.0: An Open Standard for Verified Human Identity and AI Content Provenance. The AI Lab Intelligence Unobscured, Inc., 2026. Zenodo. DOI: 10.5281/zenodo.20722378
Canonical archive
The authoritative DOI-bearing copy is on Zenodo at CERN: https://doi.org/10.5281/zenodo.20722378
This Hugging Face mirror is provided so the ML and AI research community can discover, download, and discuss the specification alongside other open AI infrastructure.
What is TIP?
TIP is a three-layer protocol: TIP-ID (identity), TIP-CONTENT (provenance), and TIP-TRUST (reputation). The cryptography is built on NIST post-quantum standards (FIPS 203 ML-KEM-768, FIPS 204 ML-DSA-65, FIPS 205 SLH-DSA). The network is a federated DAG of cryptographically signed records operated by accredited Node Operators. The governance is an independent multi-stakeholder council.
What is it not?
TIP is not a watermarking scheme, a content classifier, or a learned detection model. It is a cryptographic protocol that binds verified human identity to signed content and to a public registry record. The complementary technologies (C2PA for device-side capture, classifiers for AI-generated content detection) compose with TIP; they do not replace it.
Implementer paths
- Whitepaper: this PDF, or the canonical Zenodo DOI
- Protocol overview and architecture: theailab.org/trust-identity-protocol
- Browser plugin reference implementation: github.com/theailaborg/tip-browser-extension
- Verification portal source: github.com/theailaborg/tip-vp-with-mobile-web-app
- Verification flow and TIP-ID issuance: vp.theailab.org
Compliance
Designed to satisfy:
- EU AI Act Article 50 (AI content disclosure obligations)
- EU Digital Services Act (creator authentication and content moderation)
- GDPR (data minimisation and biometric data handling, Article 9)
- US state-level deepfake disclosure regimes
Authorship
Invented and authored by Dinesh Mendhe, Founder and Chairman, The AI Lab Intelligence Unobscured, Inc. ORCID: 0000-0003-1158-3259.
Licence
Whitepaper released under CC BY 4.0. The protocol licence (TIPCL-1.0) and the source-code repositories are licensed separately; see each repository for its specific terms.