中文摘要：

随着数据分析和发布等应用需求的出现和发展,如何保护隐私数据和防止敏感信息泄露成为当前面临的重大挑战.信息化和网络化的高速发展使得大数据成为当前学术界和工业界的研究热点,是IT业正在发生的深刻技术变革.但它在提高经济和社会效益的同时,也为个人和团体的隐私保护以及数据安全带来极大风险与挑战.大数据隐私以及数据挖掘中的隐私问题是信息安全领域目前的一个研究热点.差分隐私作为一种严格的和可证明的隐私定义,自诞生以来便受到了相当关注.介绍了隐私保护的变化和发展,对差分隐私保护技术的基本原理和特征进行了阐述,分析了差分隐私保护模型相对于传统安全模型的优势,并对其在数据发布与数据挖掘中的应用研究作了相应介绍.在对已有技术深入对比分析的基础上,展望了差分隐私保护技术的未来发展方向.

英文摘要：

As the emergence and development of application requirements such as data analysis and data publication, a challenge to those applications is to protect private data and prevent sensitive information from disclosure. With the high-speed development of information and network, big data has become a hot topic in both the academic and industrial research, which is regarded as a new revolution in the field of information technology. However, it brings about not only significant economic and social benefits, but also great risks and challenges to individuals＇ privacy protection and data security. People on the Internet leave many data footprint with cumulatively and relevance. Personal privacy information can be found by gathering data footprint in together. Malicious people use this information for fraud. It brings many trouble or economic loss to personal life. Privacy preserving, especially in data release and data mining, is a hot topic in the information security field. Differential privacy has grown rapidly recently due to its rigid and provable privacy guarantee. We analyze the advantage of differential privacy model relative to the traditional ones, and review other applications of differential privacy in various fields and discuss the future research directions. Following the comprehensive comparison and analysis of existing works, future research directions are put forward.