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Semantic-Aware-Shilling-Attacks
Semantic-Aware-Shilling-Attacks PublicIn this paper, we introduce SAShA, a new attack strategy that leverages semantic features extracted from a knowledge graph in order to strengthen the efficacy of the attack to standard CF models. W…
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sisinflab/adversarial-recommender-systems-survey
sisinflab/adversarial-recommender-systems-survey PublicThe goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show an…
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sisinflab/elliot
sisinflab/elliot PublicComprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
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sisinflab/MSAP
sisinflab/MSAP PublicIn this work, we extend the FGSM method proposing multistep adversarial perturbation (MSAP) procedures to study the recommenders’ robustness under powerful methods. Letting fixed the perturbation m…
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sisinflab/Visual-Adversarial-Recommendation
sisinflab/Visual-Adversarial-Recommendation Publicwe present an evaluation framework, named Visual Adversarial Recommender (\var), to empirically investigate the performance of defended or undefended DNNs in various visually-aware item recommendat…
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