Abstract:Abstract. The existing robust collaborative recommendation algorithms have low robustness against PIA and AoP attacks. Aiming at the problem, we propose a robust recommendation method based on shilling attack detection and matrix factorization model. Firstly, the type of shilling attack is identified based on statistical characteristics of attack profiles. Secondly, we devise corresponding unsupervised detection algorithms for standard attack, AoP and PIA, and the suspicious users and items are flagged. Finall… Show more
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