On the resilience of Collaborative Learning-based Recommender Systems Against Community Detection Attack

arXiv:2306.08929v2 Announce Type: replace-cross
Abstract: Collaborative-learning-based recommender systems emerged following the success of collaborative learning techniques such as Federated Learning (FL) and Gossip Learning (GL). In these systems, users participate in the training of a recommender system while maintaining their history of consumed items on their devices. While these solutions seemed appealing for preserving the privacy of the participants at first glance, recent studies have revealed that collaborative learning can be vulnerable to various privacy attacks. In this paper, we …

arxiv attack community cs.cr cs.ir cs.lg cs.si detection devices federated federated learning history recommender systems resilience system systems techniques training