Scalable Discovery and Continuous Inventory of Personal Data at Rest in Cloud Native Systems

AbstractCloud native systems are processing large amounts of personal data through numerous and possibly multi-paradigmatic stores (e.g., relational non-relational databases). From a privacy engineering perspective, core challenge is to keep track all exact locations, where being stored, as required by regulatory frameworks such the European General Data Protection Regulation. In this paper, we present Teiresias, comprising i) workflow pattern for scalable discovery at rest, ii) cloud system architecture open source prototype implementation said pattern. To end, enable continuous inventory featuring transparency accountability following DevOps/DevPrivOps practices. particular, scope version-controlled Infrastructure Code definitions, cloud-based storages, how integrate process into CI/CD pipelines. Thereafter, provide iii) comparative performance evaluation demonstrating both appropriate execution times real-world settings, promising detection accuracy outperforming existing proprietary tools in public clouds.KeywordsPrivacyData protectionTransparencyAccountabilityData loss preventionPrivacy engineeringDevOps