A Problem-Based Approach for Computer-Aided Privacy Threat Identification

Recently, there has been an increase of reported privacy threats hitting large software systems. These threats can originate from stakeholders that are part of the system. Thus, it is crucial for software engineers to identify these privacy threats, refine these into privacy requirements, and design solutions that mitigate the threats.

In this paper, we introduce our methodology named Problem-Based Privacy Analysis (ProPAn). The ProPAn method is an approach for identifying privacy threats during the requirements analysis of software systems using problem frame models. Our approach does not rely entirely on the privacy analyst to detect privacy threats, but allows a computer aided privacy threat identification that is derived from the relations between stakeholders, technology, and personal information in the system-to-be.

To capture the environment of the system, e.g., stakeholders and other IT systems, we use problem frames, a requirements engineering approach founded on the modeling of a machine (system-to-be) in its environment (e.g. stakeholders, other software). We define a UML profile for privacy requirements and a reasoning technique that identifies stakeholders, whose personal information are stored or transmitted in the system-to-be and stakeholders from whom we have to protect this personal information. We illustrate our approach using an eHealth scenario provided by the industrial partners of the EU project NESSoS.