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中文摘要：
针对社交网络中用户通过兴趣度匹配进行交友而产生的敏感信息泄露问题，设计了基于隐私属性的隐私保护兴趣度匹配方案。该方案利用BloomFilters来获取双方兴趣爱好集合元素的交集，确定双方兴趣爱好的匹配程度，满足匹配要求的双方可以根据意愿互相添加为好友；方案基于半诚实模型，采用密码协议来保护数据的安全性，防止恶意用户非法获取用户敏感信息，避免造成信息的滥用和泄露。理论分析及运算结果均表明，该方案运行时间具有线性复杂度，并且可以支持较大规模数据集，可有效应用于信息种类繁杂、数据内容庞大的网络环境，满足用户实时高效的现实需求。
英文摘要：
Concerning the sensitive information leakage problem resulted from making friends by interest matching in social network, a privacy preserving interest matching scheme based on private attributes was proposed. Bloom Filters were used to get the intersection of interest set for both sides, and the interest matching level was determined in the proposed scheme. Both sides intended to add each other as a friend according to their will as long as they met the matching requirements. Based on the semi-honest model, the cryptographic protocols were adopted to protect data security for preventing malicious users obtaining sensitive information illegally, which could avoid information abuse and leakage. Theoretical analysis and calculation results show that the proposed scheme has linear complexity about operational time, support large-scale data sets, and can be applied in Internet environments with different kinds of information and great number of data content, meet user＇s demands of real-time and efficiency.
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