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Ecosystem Trust Profiles

Christoph F. Strnadl

TL;DR

A novel rigorous definition of cross-data space interoperability is proposed that allows the proposition that the extent of interoperability between two data spaces is exactly determined by the amount of commonality in their respective ecosystem trust profiles to be proved.

Abstract

We define a method how digital ecosystems (including data spaces) may autonomously define and "advertise" credentials they issue or they trust in the form of so-called ecosystem trust profiles. An ecosystem trust profile collects all (verifiable) credentials and issuers sorted by trust scope accepted ("trusted") by a particular ecosystem. We then show how a minimal trust relation between ecosystems may be defined using ecosystem trust frameworks of different ecosystems and explore a few of its properties. A first application of the theory is given for a use case in the manufacturing realm where different international ecosystems need to agree on certain credentials for various scopes of trust such as identity, service compliance, and other conformance standards. We implement this requirement by identifying and discussing two different definitions of credential equivalence for a given trust scope, one requiring additional cross-ecosystem governance or coordination, one not. The second approach demonstrates how to solve the so-called cross-ecosystem trust dilemma, that is, the problem how ecosystems can establish cross-ecosystem trust while, at the same time, allowing them to fully retain their sovereignty. A fragility theorem demonstrates that this sovereignty leads trust to be unstable without any additional coordination or governance mechanisms on top of (and outside to) ecosystem trust profiles. We extend our method to data spaces in particular and propose a novel rigorous definition of cross-data space interoperability. This allows us to prove the proposition that the extent of interoperability between two data spaces is exactly determined by the amount of commonality in their respective ecosystem trust profiles.

Ecosystem Trust Profiles

TL;DR

A novel rigorous definition of cross-data space interoperability is proposed that allows the proposition that the extent of interoperability between two data spaces is exactly determined by the amount of commonality in their respective ecosystem trust profiles to be proved.

Abstract

We define a method how digital ecosystems (including data spaces) may autonomously define and "advertise" credentials they issue or they trust in the form of so-called ecosystem trust profiles. An ecosystem trust profile collects all (verifiable) credentials and issuers sorted by trust scope accepted ("trusted") by a particular ecosystem. We then show how a minimal trust relation between ecosystems may be defined using ecosystem trust frameworks of different ecosystems and explore a few of its properties. A first application of the theory is given for a use case in the manufacturing realm where different international ecosystems need to agree on certain credentials for various scopes of trust such as identity, service compliance, and other conformance standards. We implement this requirement by identifying and discussing two different definitions of credential equivalence for a given trust scope, one requiring additional cross-ecosystem governance or coordination, one not. The second approach demonstrates how to solve the so-called cross-ecosystem trust dilemma, that is, the problem how ecosystems can establish cross-ecosystem trust while, at the same time, allowing them to fully retain their sovereignty. A fragility theorem demonstrates that this sovereignty leads trust to be unstable without any additional coordination or governance mechanisms on top of (and outside to) ecosystem trust profiles. We extend our method to data spaces in particular and propose a novel rigorous definition of cross-data space interoperability. This allows us to prove the proposition that the extent of interoperability between two data spaces is exactly determined by the amount of commonality in their respective ecosystem trust profiles.
Paper Structure (17 sections, 8 theorems, 22 equations, 2 figures)

This paper contains 17 sections, 8 theorems, 22 equations, 2 figures.

Table of Contents

  1. Introduction
  2. Ecosystem Trust Profiles
  3. Application
  4. Manufacturing Use Case
  5. Theoretical Extensions
  6. Top Down - Brute Force
  7. Cautious Approach - Minimal consensus
  8. A Fragility Theorem on Trust
  9. Implementation
  10. Approach
  11. Ontology
  12. Gaia-X Meta-Registry
  13. Data Spaces
  14. Data Space Trust Frameworks
  15. Necessary general conditions for data transactions
  16. ...and 2 more sections

Key Result

Lemma 1

The relation $\sqsubseteq_s$ is reflexive, that is, $E \sqsubseteq_s E$ for all $E = \langle P, S \rangle \in \mathscr{E}$ for all trust scopes $s \in S$.

Figures (2)

  • Figure 1: Catalog of ecosystems, trust service providers, and credentials (VC - verifiable credential; TSP - trust service provider)
  • Figure 2: Class diagram of the ecosystem trust ontology

Theorems & Definitions (26)

  • Definition 1: Ecosystem trust profile
  • Definition 2: Ecosystem trust relation
  • Lemma 1: Reflexivity
  • proof
  • Definition 3: Direct mutual trust
  • Definition 4: Trust realm
  • Definition 5: Credentials for a given trust scope
  • Proposition 1: Credential equivalence - Version 1
  • proof
  • Definition 6: Credential equivalence - Version 2
  • ...and 16 more