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SP, service provider, H m, helper user.
However, a helper user obtains the distances between a user and the cluster centres.
Later, the service provider disseminates the public key of the helper user to the other users.
Furthermore, since in each iteration helper user changes, deducing meaningful information from computed distances becomes infeasible.
Even though the distances are permuted and the identity of the user is unknown to the helper user, the helper user can still acquire information about the distances between clusters and the number of assignments for each cluster.
Note that while the helper user learns the distances between users and K centroids, it is not possible to know the distance between a specific user and a certain cluster since both is kept hidden from the helper user.
Similar(37)
It is clear from the figure that the number of helper users should be chosen accordingly since the computational and communication loads become heavy with fewer helper users.
Secondly, the helper users can be chosen truly random by deploying another sub-protocol.
Figure 5 Work share between the service provider and different numbers of helper users.
Notice that the way helper users perturb data prevents the service provider to obtain meaning information about each user group.
Recall that every user, including the helper users, only interacts with the service provider using a secured channel.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com