大数据环境下的隐私保护是一个亟需解决的重要课题，目前国内外在大数据隐私风险评估和溯源问责等问题上尚缺乏深度的理论研究和科学的分析模型。本项目首先运用综合交叉学科的理论和方法，从信息生命周期视角，明确大数据隐私保护的内涵及特征，并借助系统动力学构建大数据隐私生命周期模型；其次，深入分析生命周期各阶段的隐私风险，构建动态隐私攻击模型和风险监测体系，结合成本最优和动态博弈理论，建立大数据隐私风险评估机制；再次，构建大数据信息融合模型，并结合数据溯源和数字水印技术，建立大数据隐私溯源问责机制，从功能上对隐私风险评估进行反馈和完善；在此基础上，建立大数据隐私风险管理框架，为模型的应用研究提供支持，并通过有效性分析和专家访谈修正和完善研究模型。研究成果有助于丰富大数据隐私保护的理论体系与技术方法，为政府机构和企事业单位的大数据应用工作提供决策支持，进一步推动大数据和信息安全产业的发展。

Privacy related with big data has been considered as one of the greatest issues in many applications, but there are still some limits in theory research and scientific analysis model of privacy risk assessment and accountability traced in big data environment. From the perspective of information lifecycle theory, the subject defines the connotation and characteristics of big data privacy protection by interdisciplinary theories and methods, and the big data privacy lifecycle model is constructed based on dynamics system theory. Then, the privacy attack model and risk evaluation mechanism are built by the analysis of privacy risks, combined with the optimal cost and dynamic game theory. Furthermore, the privacy traceability accountability mechanism is constructed by data provenance and the digital watermarking technology based on the information fusion model of big data. At last, the privacy risk management framework of big data are studied to provide support for the application of model. This study has important significance in enriching the theoretical system and research method of the big data privacy protection, but also provides decision support for the governments and enterprises. The overall research has an important role to promote the development of big data and information security industry.