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The need for a privacy management layer in today's systems started tomanifest with the emergence of new systems for privacy-preserving analytics andprivacy compliance. As a result, many independent efforts have emerged that tryto provide system support for privacy. Recently, the scope of privacy solutionsused in systems has expanded to encompass more complex techniques such asDifferential Privacy (DP). The use of these solutions in large-scale systemsimposes new challenges and requirements. Careful planning and coordination arenecessary to ensure that privacy guarantees are maintained across a wide rangeof heterogeneous applications and data systems. This requires new solutions formanaging and allocating scarce and non-replenishable privacy resources. In thispaper, we introduce Cohere, a new system that simplifies the use of DP inlarge-scale systems. Cohere implements a unified interface that allowsheterogeneous applications to operate on a unified view of users' data. In thiswork, we further address two pressing system challenges that arise in thecontext of real-world deployments: ensuring the continuity of privacy-basedapplications (i.e., preventing privacy budget depletion) and effectivelyallocating scarce shared privacy resources (i.e., budget) under complexpreferences. Our experiments show that Cohere achieves a 6.4--28x improvementin utility compared to the state-of-the-art across a range of complexworkloads.

Cohere: Managing Differential Privacy in Large Scale Systems