Personal Privacy Metrics (P-PM) represent the means to increase the user’s awareness. This component collects, computes and shares easy-to-understand data to allow users know how a service (e.g., a data buyer) stores and manages the data, if it shares it with third parties, how secure and transparent it looks, etc. These are all fundamental pieces of information for a user to know to take informed decisions. The PM computes this information via a standard REST interface, offering an open knowledge information system which can be queried using an open and standard platform. PMs combine information from supervised machine learning analytics, services themselves and domain experts, volunteers, and contributors.
Its implementation builds on MongoDB (for the database), Python/Flask and Swagger (for the server).
