Attacking Recommender Systems: A Cost-Benefit Analysis
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...
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Veröffentlicht in: | IEEE intelligent systems 2007-05, Vol.22 (3), p.64-68 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 1541-1672 1941-1294 |
DOI: | 10.1109/MIS.2007.44 |