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.20722378This 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.
