计算机科学 ›› 2017, Vol. 44 ›› Issue (5): 81-88.doi: 10.11896/j.issn.1002-137X.2017.05.015
鲜征征,李启良,李改,李磊
XIAN Zheng-zheng, LI Qi-liang, LI Gai and LI Lei
摘要: 利用背景知识间接推导出个人隐私信息已成为Internet用户更担忧的问题,定义极为严格且可证明的差分隐私保护是目前解决该问题的最有效的隐私保护技术。Berlioz等将差分隐私保护技术应用于协同过滤算法之一的矩阵分解中,虽然提出了新的算法,但是缺少严格的证明过程。针对他们提出的算法,将补充相应的数学证明,然后 将Chaudhuri等提出的目标函数加扰方法灵活应用于ALS目标函数中。此外,还给出一种差分隐私保护参数的选择方案。最后,在两个真实数据集上的实验验证结果表明,所提出的ALS目标函数加扰方法取得了更好的推荐效果。
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