Mohan Li1, Yanbin Sun1, *, Shen Su1, Zhihong Tian1, Yuhang Wang1, *, Xianzhi Wang2
CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 331-344, 2019, DOI:10.32604/cmc.2019.05379
Abstract Maliciously manufactured user profiles are often generated in batch for shilling attacks. These profiles may bring in a lot of quality problems but not worthy to be repaired. Since repairing data always be expensive, we need to scrutinize the data and pick out the data that really deserves to be repaired. In this paper, we focus on how to distinguish the unintentional data quality problems from the batch generated fake users for shilling attacks. A two-steps framework named DPIF is proposed for the distinguishment. Based on the framework, the metrics of homology and suspicious degree More >
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