移动社会媒体大数据共享交换中的隐私保护研究

移动社会媒体大数据具有实时、多源、异构等特性，存在着难以估量的潜在价值，并驱动着移动社会媒体蓬勃发展。目前，移动社会媒体大数据面临“用户隐私安全需求难满足、隐私模型难设计、安全访问控制难实现”等问题，导致无法有效保障用户的隐私安全，并促进数据间的共享交换。针对前述难题，本项目拟结合差分隐私、机器学习、密码学、区块链等技术，研究移动社会媒体中的隐私安全度设置、隐私保护模型与数据的访问控制等核心问题，提出“双自主隐私安全度标签设置、隐私策略库自主调用、安全有效的角色基访问控制及其用户权限验证”的移动社会媒体安全管理方案，并构建移动社会媒体大数据安全共享交换平台，以支撑移动社会媒体的深层次发展与应用。本项目的研究成果将为移动社会媒体大数据共享交换中的隐私保护奠定理论与技术基础。

Big data of mobile social media has the characteristics of real-time, multi-source and heterogeneous, and also has inestimable potential value, which drives the vigorous development of mobile social media. Nowadays, researches on big data of mobile social media are facing difficulties in meeting users’ needs in privacy protection, designing owners’ privacy model, and achieving secure access control, which cannot effectively protect the privacy of users and promote data sharing and exchange. To further support the deep development and application of mobile social media, this project intends to address above problems. Specifically, (1) combine multiple technologies (including differential privacy, machine learning, cryptography, blockchain) to study the core issues of privacy settings, privacy protection and data access control in mobile social media, (2) propose secure management scheme for mobile social media data which owns dual independent privacy label settings, self-invocation privacy policy library, and (3) present secure and effective role-based access control and user privilege verification. In the end, (4) build a secure sharing and exchange platform for the big data of mobile social media. The research results of this project will lay a theoretical and technical foundation for privacy protection in the sharing and exchange of big data of mobile social media.