Estimating Performance Costs of Enabling Privacy-Awareness in Data Lifecycles
摘要
Privacy-awareness is a mandatory requirement for data management systems. When planning for compliance of existing systems, performance issues have to be considered: in this paper we propose an approach for evaluating performance costs of enabling privacy-awareness in data lifecycles based on risk analysis and queuing networks. We use as running example a case of monitoring for smart cities, starting from an existing case to provide a guideline for practitioners to show how to use simple performance models to evaluate the impact of an intervention to guarantee privacy compliance, exploiting a well-known, state-of-the-art, free, event-based simulator, namely Java Modeling Tools, to avoid practitioners the need for analytical models and related complexity.