Homomorphic Encryption for Data Privacy and Security
Practical Solutions and Value
Ensuring data privacy and security during computational processes presents a significant challenge, particularly when using cloud services. Traditional encryption methods require data to be decrypted before processing, exposing it to potential risks. Homomorphic encryption offers a promising solution, allowing computations on encrypted data without revealing the underlying information.
Apple introduces a new open-source Swift package, swift-homomorphic-encryption, to implement this cryptographic technique. This package enables computation on encrypted data without decrypting it or accessing the decryption key. Clients can send encrypted data to a server, which processes the data and returns an encrypted result that the client can decrypt. This approach maintains data privacy and security throughout the computational process, making it ideal for cloud services.
Key Features of swift-homomorphic-encryption
- Swift on Server: Utilizing the Hummingbird HTTP framework and cross-platform support.
- Benchmark Library: For easy benchmarking of performance.
- Swift Crypto: Providing performant low-level cryptography primitives.
The implementation uses the Brakerski-Fan-Vercauteren (BFV) HE scheme, based on the ring learning with errors (RLWE) hardness problem, ensuring post-quantum 128-bit security. This enables secure computation on encrypted data and protects against both classical and potential future quantum attacks.
Apple utilizes homomorphic encryption in iOS 18’s Live Caller ID Lookup feature, providing caller ID and spam blocking services by sending an encrypted query to a server that retrieves information about a phone number without knowing the specific phone number in the request. The live-caller-id-lookup-example backend demonstrates this functionality, highlighting the practical application of homomorphic encryption.
The Live Caller ID Lookup feature also relies on Private Information Retrieval (PIR), allowing clients to perform private key-value database lookups. This efficient approach supports very large databases with frequent updates, enhancing data privacy and security.
Empowering Developers and Researchers
The swift-homomorphic-encryption package empowers developers and researchers to create privacy-preserving applications within and beyond the Apple ecosystem. Potential applications include private set intersection, secure aggregation, and machine learning. The community is encouraged to contribute to the project and explore new use cases for homomorphic encryption, fostering innovation and enhancing data security.
