Faster Private Rating Update via Integer-Based Homomorphic Encryption

Pranav Verma, Anish Mathuria, Sourish Dasgupta

Abstract: In encryption-based privacy-preserving recommender systems (PPRS), the user sends encrypted ratings to the server. An encrypted rating vector can have thousands of ciphertexts, causing a communication overhead. In some encryption-based PPRS proposed in the literature, if a user wants to rate a single item, he/she is required to send the entire rating vector to hide which item was rated. A user’s rating value and the item that is being rated both should remain private. This can be seen as a variant of the classical PIR-write problem. The goal is that each time a user wants to modify any data block, the communication should be minimal from the user.