Slope One with Privacy
The targeted users and customers are all the Internet actors providing
personalized services to their users, interested by integrating
recommender systems that are more respectful of their privacy.
SlopPy (for Slope One with Privacy )  is both a
privacy-preserving version of the recommendation algorithm Slope One and
a recommendation architecture built around this algorithm in which a
user never releases directly his personal information (i.e., his
ratings) to a trusted third party. The figure below illustrates the architecture of the SlopPy recommender system.
More precisely in SlopPy, each user first perturbs locally his
data (Step 1) by applying a Randomized Response Technique (RRT) before
sending this information to the entity responsible for storing this
information through an anonymous communication channel (Step 2). This entity is assumed to be semi-trusted, also sometimes called
honest-but-curious in the sense that it is assumed to follow the
directives of the protocol (i.e., it will not corrupt the
perturbed ratings sent by a user or try to influence the output of the
recommendation algorithm) but nonetheless tries to extract as much
information as it can from the data it receives. Out of the perturbed ratings, the semi-trusted entity constructs two
matrices (i.e., the deviation matrix and the cardinality matrix)
following the Weighted Slope One algorithm (Step 3). When a user needs a recommendation on a particular movie, he queries
these matrices through a variant of a private information retrieval
scheme (Step 4) hiding the content of his query (i.e., the item
he is interested in) to the semi-trusted entity. By combining the data retrieved (Step 5) with his true ratings (which
once again are only stored on his machine), the user can then locally
compute the output of the recommendation algorithm for this particular
item (Step 6).
 Sébastien Gambs and Julien Lolive. SlopPy: Slope One with Privacy. In DPM, September 2012.
SlopPy is currently available as a prototype only. It can be released and supplied under license on a case-by-case basis.