Get more info at http://cap-platform.github.io

1. CAPP
Context Aware Privacy Platform
We are:
Marie-José Bonthuis
Eds Keizer
Martijn Veening
Lykle de Vries
2016

2. What is CAPP?
With CAPP, we intend to research ways of providing information
belonging to an individual to someone else, without the need for
large centralized databases, without leaving (traces of) data behind
that might make that individual vulnerable.

3. Assumptions
• Privacy first;
• Intervention driven;
• Very small scope for proof of concepts;
• Data minimalistic approach;

4. Assumptions (2)
• Communication of relevant attributes instead of persistent
registration of unnecessary data;
• Usage of AI to ascertain reliability of data;
• Scalable.

5. Platform
• Open source (license CC);
• Distributed architecture;
• Use cases are based on information supply chain;
• Identifaction;
• Trust of data sources (input / output).

6. Smart
Artificial Intelligence
• Inference engine;
• Fuzzy logic to present result (weighed aggregation).

7. Challenges
Practical:
• Identifying the subject with (very) high certainty.
Technical:
• Distributed data storage;
• Protocol specifications.

8. Use case
ICE-d: In Case of Emergency data

9. What
CAPP can be used to identify conflicts when an intervention (like an
MRI) is proposed to a patient.

10. How
Medical professionals use the platform to request attributes of the
patient, identified by their (temporary) ID or token.

11. Example
• the doctor is authenticated and authorized to request the data
(within a defined scope);
• the patient can be identified using a (temporary) id;
• the request can be 'Is MRI possible (for this patient)?';
• the result can be simple answers with metadata (age / quality of
the source): yes / unclear / no.