Secure Federated Computing
Keywords:
confidentiality-preserving computation, edge computing, collaborative computing, cryptology, secure collaborative computationAbstract
The concept of safeguarding privacy in computations, known as Privacy-Preserving Computation (PPC), involves the encrypted processing of confidential data. Despite its theoretical advantages, the intricate technology poses significant practical entry barriers. In this context, we establish design objectives and principles for a middleware that centralizes demanding cryptographic processes on the server side while offering a user-friendly interface for client-side application developers. The resultant framework, termed "Federated Secure Computing," delegates computationally intensive tasks to the server, segregating cryptographic concerns from business logic. Through an Open API 3.0 definition, it delivers microservices and accommodates various protocols via self-discovered plugins. Notably, it demands only minimal DevSecOps capabilities, ensuring simplicity and security. Moreover, its compact size makes it suitable for deployment in the Internet of Things (IoT) and introductory scenarios on consumer hardware. Benchmarks for calculations using a Secure Multiparty Computation (SMPC) protocol, applied to both vertically and horizontally partitioned data, reveal swift runtimes in seconds across dedicated workstations and IoT devices like Raspberry Pi or smartphones. The reference implementation is accessible as free and open-source software under the MIT license.
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