Manipulating Recommender Systems: A Comprehensive Survey of Poisoning Attacks and Countermeasures

Poisoning attacks on recommender systems pose a serious threat by manipulating the training data to corrupt the integrity of the underlying models, leading to biased recommendations that benefit the attacker's goals.