Developer’s Checklist: How to Build an FHE Application

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For most developers, fully homomorphic encryption (FHE) application development is uncharted territory. FHE allows you to compute on data without ever decrypting it, which means that organizations can pool sensitive data to create smarter ML models, or build cloud-based encrypted anomaly detection models without ever exposing data in the clear. In practice, building such applications asks you to deal with a host of parameters that aren’t relevant to traditional programming, including noise budgets, polynomial approximations, ciphertext packing and parameter tradeoffs. It’s all a lot to take in, but you can tackle FHE development just like an elephant sandwich: One bite at a time. Here is my checklist for how to approach FHE application development. By following this guide, you can take your first steps toward never exposing your sensitive data in the cloud again. Step 1: Design Your Architecture for a Clean Client-Server Handoff FHE applications follow a strict client-server pattern. The client encrypts plaintext data and hands it over to the server. The server performs computations on the encrypted data and hands it back. The keys never leave the client, and only the client can read the results. Practically, that means no peeking. The server must be able to perform the required calculations without querying the client mid-computation. All data takes a single round trip: The server can never ‘decide what to do next’ based on the results of a computation. An FHE application can have multiple clients and a single server; that’s how federated learning works. In this case, you …

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