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Enforcing data protection and privacy rules within large data processingapplications is becoming increasingly important, especially in the light ofGDPR and similar regulatory frameworks. Most modern data processing happens ontop of a distributed storage layer, and securing this layer against accidentalor malicious misuse is crucial to ensuring global privacy guarantees. However,the performance overhead and the additional complexity for this is oftenassumed to be significant -- in this work we describe a path forward thattackles both challenges. We propose "Software-Defined Data Protection" (SDP),an adoption of the "Software-Defined Storage" approach to non-performanceaspects: a trusted controller translates company and application-specificpolicies to a set of rules deployed on the storage nodes. These, in turn, applythe rules at line-rate but do not take any decisions on their own. Such anapproach decouples often changing policies from request-level enforcement andallows storage nodes to implement the latter more efficiently.  Even though in-storage processing brings challenges, mainly because it canjeopardize line-rate processing, we argue that today's Smart Storage solutionscan already implement the required functionality, thanks to the separation ofconcerns introduced by SDP. We highlight the challenges that remain, especiallythat of trusting the storage nodes. These need to be tackled before we canreach widespread adoption in cloud environments.

Towards Software-Defined Data Protection: GDPR Compliance at the Storage Layer is Within Reach