中文摘要：

随着移动互联网、云计算和大数据技术的广泛应用,电商、搜索、社交网络等服务在提供便利的同时,大数据分析使用户隐私泄露的威胁日益凸显,不同系统隐私保护策略和能力的差异性使隐私的延伸管理更加困难,同一信息的隐私保护需求随时间变化需要多种隐私保护方案的组合协同。目前已有的各类隐私保护方案大多针对单一场景,隐私缺乏定量化的定义,隐私保护的效果、隐私泄露的利益损失以及隐私保护方案融合的复杂性三者之间的关系刻画缺乏系统的计算模型。因此,在分析隐私保护研究现状的基础上,提出隐私计算的概念,对隐私计算的内涵加以界定,从隐私信息的全生命周期讨论隐私计算研究范畴,并从隐私计算模型、隐私保护场景适应的密码理论、隐私控制与抗大数据分析的隐私保护、基于信息隐藏的隐私保护以及支持高并发的隐私保护服务架构等方面展望隐私计算的发展趋势。

英文摘要：

With the widespread application of mobile Internet, cloud computing and big data technologies, people enjoy the convenience of electronic business, information retrieval, social network and other services, whereas the threats of privacy leaks are ever growing due to the use of big data analytics. The differences of privacy protection strategy and ability in different systems bring more difficulties in privacy extended management. In addition, the requirements of protecting the same information at different time need the combination of various privacy protection schemes. However, nearly all the current privacy protection schemes are targeting at a single case, which lacks systematic and quantized privacy characterization. Furthermore, there is no systematic computing model describing the relationship between the protection level, profit and loss of privacy leaks and the complexity of integrated privacy protection methods. Based on the analysis on the research status of privacy protection, the concept and connotation of privacy computing is proposed and defined. Then the privacy computing research category will be discussed from the whole life cycle of information privacy protection. Finally, some research directions of privacy computing are given, including privacy computing model, context adaptive cryptology for privacy protection, big data analytics resisted privacy control and protection, privacy protection based on information hiding and system architecture for high concurrent privacy preserving services.