Homomorphic Encryption for ML
by Community · free · Last verified 2026-03-17
Enables computation on encrypted data so that ML inference or training can be performed without decrypting sensitive inputs, providing cryptographic confidentiality guarantees. Emerging technique for privacy-preserving AI inference in regulated industries such as healthcare and finance.
https://github.com/microsoft/SEAL ↗C
C—Below Average
Adoption: CQuality: AFreshness: ACitations: BEngagement: F
Specifications
- License
- MIT
- Pricing
- free
- Capabilities
- CKKS-scheme, BFV-scheme, encrypted-inference, secure-multi-party-computation, bootstrapping
- Integrations
- Microsoft SEAL, OpenFHE, Concrete ML, TenSEAL
- Use Cases
- Medical AI inference on encrypted patient records, Encrypted financial risk scoring, Privacy-preserving biometric authentication
- API Available
- No
- Difficulty
- advanced
- Prerequisites
- cryptography, linear-algebra, machine-learning
- Supported Agents
- Tags
- homomorphic-encryption, privacy, secure-computation, cryptography
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
49.8Adoption
42
Quality
80
Freshness
82
Citations
68
Engagement
0