Monitoring and checking privacy policies of cloud services based on models

Abstract

Data geo-location policies constrain the geographical locations at which personal data may be stored or processed. Data storage and processing locations are dynamically changed by cloud elasticity that migrates and replicates cloud services across data centers. Thus, cloud elasticity as well as data transfers of interacting services may re-locate data, which potentially violates data geo-location policies. To detect these violations, we develop a policy checking approach based on runtime models. We examine monitoring and model updating mechanisms for reflecting service composition and deployment changes caused by elasticity. Based on the updated runtime model we derive potential data transfers and check them against policies. Initial results indicate the effectiveness and high-performance of our approach.