Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios. (arXiv:2204.13594v2 [cs.IR] UPDATED)

Various attack methods against recommender systems have been proposed in the
past years, and the security issues of recommender systems have drawn
considerable attention. Traditional attacks attempt to make target items
recommended to as many users as possible by poisoning the training data.
Benifiting from the feature of protecting users' private data, federated
recommendation can effectively defend such attacks. Therefore, quite a few
works have devoted themselves to developing federated recommender systems. For
proving current federated recommendation is still vulnerable, …

deep learning ir poisoning