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Jordan Vega
Google has announced the release of PipelineDP4j, a differential privacy solution that enables developers to execute highly parallelizable computations using Java while ensuring personal information remains private and secure.
This new tool is designed to be usable by all developers, regardless of their expertise in differential privacy, and can be used with Java, Kotlin, or Scala. PipelineDP4j supports distributed data processing frameworks such as Apache Beam and, soon, Apache Spark. By reducing the barrier of entry for developers, Google aims to open the door for new applications of differential privacy.
PipelineDP4j is an evolution of Google's work with OpenMined, which builds open-source privacy software. With this release, Google now covers some of the most popular languages, including Python, Java, Go, and C++, potentially reaching over half of all developers worldwide. The solution relies on lower-level building blocks from the differential privacy library, combining them into an out-of-the-box solution that takes care of essential steps for differential privacy.
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