Fundamentally, vector search like this doesn't have a concept of something "matching" or "not matching". It's just a cosine similarity value. To determine if an image "matches", you have to check if that similarity is within some given threshold. If the results of the cosine similarity operation are encrypted (they are with HE), that wouldn't be possible to determine.
The bigger privacy risk would be that the device routes the request to a specific database shard based on whichever has a center-point closest to the image embedding on the device. They take steps to protect this information such as third-party proxying to hide user IP addresses, as well as having devices send fake requests so that the server cannot tell which are real user data and which are fake data.
Fundamentally, vector search like this doesn't have a concept of something "matching" or "not matching". It's just a cosine similarity value. To determine if an image "matches", you have to check if that similarity is within some given threshold. If the results of the cosine similarity operation are encrypted (they are with HE), that wouldn't be possible to determine.
The bigger privacy risk would be that the device routes the request to a specific database shard based on whichever has a center-point closest to the image embedding on the device. They take steps to protect this information such as third-party proxying to hide user IP addresses, as well as having devices send fake requests so that the server cannot tell which are real user data and which are fake data.