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In recent decades, high-utility itemset mining (HUIM) has emerging a critical research topic since the quantity and profit factors are both concerned to mine the high-utility itemsets (HUIs). Generally, data mining is commonly used to discover interesting and useful knowledge from massive data. It may, however, lead to privacy threats if private or secure information (e.g., HUIs) are published in the public place or misused. In this paper, we focus on the issues of HUIM and privacy-preservingdoi:10.1016/j.pisc.2015.11.013 fatcat:t5y7zxkhkzc7rpdopq7gbs4lwi