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In shilling attacks, an adversarial party injects a few fake user profilesinto a Recommender System (RS) so that the target item can be promoted ordemoted. Although much effort has been devoted to developing shilling attackmethods, we find that existing approaches are still far from practical. In thispaper, we analyze the properties a practical shilling attack method should haveand propose a new concept of Cross-system Attack. With the idea of Cross-systemAttack, we design a Practical Cross-system Shilling Attack (PC-Attack)framework that requires little information about the victim RS model and thetarget RS data for conducting attacks. PC-Attack is trained to capture graphtopology knowledge from public RS data in a self-supervised manner. Then, it isfine-tuned on a small portion of target data that is easy to access toconstruct fake profiles. Extensive experiments have demonstrated thesuperiority of PC-Attack over state-of-the-art baselines. Our implementation ofPC-Attack is available at https://github.com/KDEGroup/PC-Attack.

Practical Cross-System Shilling Attacks with Limited Access to Data