From 3425a5fd77a906524929c3bb55a7d68388fbf9f7 Mon Sep 17 00:00:00 2001 From: Sefik Ilkin Serengil Date: Fri, 11 Jul 2025 12:16:58 +0100 Subject: [PATCH] Update README.md encrypt embeddings section update --- README.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index c3b57d3..e1244ea 100644 --- a/README.md +++ b/README.md @@ -315,7 +315,9 @@ Conversely, if your task involves facial recognition on small to moderate-sized **Encrypt Embeddings** - [`Demo with PHE`](https://youtu.be/8VCu39jFZ7k), [`Tutorial for PHE`](https://sefiks.com/2025/03/04/vector-similarity-search-with-partially-homomorphic-encryption-in-python/), [`Demo with FHE`](https://youtu.be/njjw0PEhH00), [`Tutorial for FHE`](https://sefiks.com/2021/12/01/homomorphic-facial-recognition-with-tenseal/) -Vector embeddings, though not reversible, carry sensitive information like fingerprints, making their security crucial. Encrypting them prevents adversarial misuse. Traditional encryption (e.g., AES) is secure but unsuitable for cloud-based distance calculations. [Homomorphic encryption](https://youtu.be/3ejI0zNPMEQ) allows computations on encrypted data without revealing content—ideal for secure cloud processing. For example, the cloud can compute encrypted similarity without knowing the data, while only the key holder can decrypt the result. See the [`LightPHE`](https://github.com/serengil/LightPHE) library for partially homomorphic encryption (PHE). +Vector embeddings, though not reversible, carry sensitive information like fingerprints, making their security crucial. Encrypting them prevents adversarial misuse. Traditional encryption (e.g., AES) is secure but unsuitable for cloud-based distance calculations. + +[Homomorphic encryption](https://youtu.be/3ejI0zNPMEQ) allows computations on encrypted data without revealing content—ideal for secure cloud processing. For example, the cloud can compute encrypted similarity without knowing the data, while only the key holder can decrypt the result. See the [`LightPHE`](https://github.com/serengil/LightPHE) library for partially homomorphic encryption. ```python from lightphe import LightPHE