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Sefik Ilkin Serengil 2025-03-07 11:19:52 +00:00 committed by GitHub
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@ -383,7 +383,6 @@ from lightphe import LightPHE
# define a plain vectors for source and target
alpha = DeepFace.represent("img1.jpg")[0]["embedding"] # user tower
beta = DeepFace.represent("target.jpg")[0]["embedding"] # item tower
expected_similarity = sum(x * y for x, y in zip(alpha, beta))
# build an additively homomorphic cryptosystem (e.g. Paillier) on-prem
cs = LightPHE(algorithm_name = "Paillier", precision = 19)
@ -416,9 +415,6 @@ calculated_similarity = cs.decrypt(encrypted_cosine_similarity)[0]
# verification
threshold = 0.68 # cosine distance threshold for VGG-Face and cosine
print("same person" if calculated_similarity >= 1 - threshold else "different persons")
# proof of work
assert abs(calculated_similarity - expected_similarity) < 1e-2
```
In this scheme, we leverage the computational power of the cloud to compute encrypted cosine similarity. However, the cloud has no knowledge of the actual calculations it performs. Only the secret key holder on the on-premises side can decrypt the encrypted cosine similarity and determine whether the pair represents the same person or different individuals.