An Intellyx Brain Candy Brief
Homomorphic encryption allows encrypted data to be consumed directly for analytics and processing without first having to decrypt it.
Without homomorphic encryption, encrypted data at rest has first to be decrypted for processing or analysis, and re-encrypted before it’s stored again if modified. Encrypting and decrypting sensitive data to protect against breaches impacts application performance.
Researchers have been working on homomorphic encryption for several years to reduce or eliminate this performance impact, using various approaches. The base technology is now in its fourth generation.
Heaan’s homomorphic encryption solution uses the CKKS approach, a fourth-generation scheme that works well with numbers, such as vector data types for example.
They call their homomorphic encryption product enVector because it encrypts vector data for storage, securing vector data at rest, and supports vector search operations on the encrypted vector data.
Organizations use enVector for securely adopting AI solutions such as LLMs, RAG, and biometric authentication that are enabled using vector embeddings, which can often include sensitive data such as health records, PII, and facial recognition features.
The enVector product lets you run machine learning models, analytics, and vector searches on sensitive data, while keeping it fully encrypted.
Heaan emphasizes the performance of their encryption and decryption solutions, which are enhanced with GPU processing. A demo site is available for customers to try out their technology.
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