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- W2004149199 abstract "A work highlights the lack of robustness collaborative recommender systems exhibit against attack. This vulnerability can lead to significantly biased recommendations for target items. Here, we examine such attacks from a cost perspective, focusing on how attack size - that is, the number of ratings inserted - affects attack success. We introduce a framework for quantifying the gains attackers realize, taking into account the financial cost of mounting the attack. A cost-benefit analysis of third-party attacks on recommender systems shows that attackers realize profits even when incurring costs associated with rating insertions." @default.
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- W2004149199 date "2007-05-01" @default.
- W2004149199 modified "2023-10-17" @default.
- W2004149199 title "Attacking Recommender Systems: A Cost-Benefit Analysis" @default.
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- W2004149199 doi "https://doi.org/10.1109/mis.2007.44" @default.
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