Trust in Network Society

This work is carried out in collaboration with NLnet and begins with the founding ideas in these works:

Trust semantic learning and monitoring is part of a wide ranging effort to understand trust in network socio-technical systems. The expected outcome of this part is a methodology and proof of concept code library for qualifying and quantifying trust between agents in a network. In IT, trust is often treated as a binary "crypto token", based on some validation test, and developers naively speak of zero trust systems without understanding the depth of what trust really is. But, trust is a deeply social phenomenon, which changes in real time based on social and technical interactions. By applying learning algorithms and data analytics to streamed interactions, this project attempts to qualify and quantify a measure of trust as a way of making realtime risk estimates.

Project outcomes

  1. Item 1, Literature summary (in progress) (pdf)
  2. Item 2, Notes on Incorporating Operational Trust Design into Automation (Companion to code examples) (pdf) (code example repository)
  3. Item 3. Promise Theory model of trust and trustworthiness (complete draft for peer review) (pdf)
  4. Item 4. Narrative Attentiveness Notes on Analysis and Assessment of Semantic Trustworthiness v0.1 (pdf)
  5. Item 5: Trust assessment examples (Notes accompanying examples and code) (pdf)
  6. Item 6: Group collaboration of users on Wikipedia A data study of trust dynamics (Notes accompanying examples and code) (pdf)
  7. Item 7: Studying attack resilience in human-machine processes using (mis)trust(worthiness) as a predictor (The security angle) (pdf)
    With preprints:
    A Promise Theory Perspective on The Role of Intent in Group Dynamics
    Group Related Phenomena In Wikipedia Edits

Program code respository

The repository for this project is on
https://github.com/markburgess/Trustability

Supplementary popular outreach, impact communication

These articles are intended to be made public where the relevant audience is.

  1. (None)
  2. Popular summary of trust model (pdf)
  3. Popular summary of trust model, part 2 (pdf)
  4. Should we trust what we read? (pdf)
  5. Trust is useful because conflict and error are human constants? (pdf)
  6. Birds of a Feather Mistrust Together (Alignment, group dynamics, drifting intentions, and the Promise Theory of Trust) (pdf)
  7. What does trust have to do with security anyway? (pdf)