本项目针对大数据环境下多源异构海量数据的安全需求，以数据安全存储为目标，从数据安全保护、多级安全两个方面进行研究，构建安全的数据存储模型和方法。在数据安全保护方面，针对多源异构的数据安全存储问题，研究基于公钥加密的数据存储方法，提高检索效率，减小计算复杂度，解决多源异构密文检索的难题。针对大规模数据，研究基于全同态加密的数据存储算法，解决加密后数据难以搜索的问题，并通过采用整数和多项式方法简化全同态加密算法复杂度，提高算法效率。在数据多级安全方面，研究数据的多级安全存储模型和方法，实现不同安全级别数据间的安全隔离；并通过分析系统处理过程中的信息流，制定信息流安全策略，保证数据处理过程中信息的安全交互。本项目的研究在保证多源异构数据存储安全的同时，将提高数据检索的效率，实现不同安全级别数据间的安全交互，为云计算技术发展提供安全支撑。

To address the security requirements of multi-source heterogeneous and large-scale data in the context of big data, the secure data storage model and method are proposed according to the research on data cipher text retrieval and multi-level security. In the matter of data protection, for the heterogeneous data with multiple sources , the data storage method based on public key encryption are researched to improve retrieval efficiency and reduce computational complexity also as to solve the problem of multi-source heterogeneous cipher text. For the massive homeomorphic data, the data storage algorithms based on full homomorphic encryption are studied to solve the problem that the cipher text is difficult to search massive data. Also the algorithm complexity is simplified and algorithm efficiency is improved through employing Integer and Polynomial method. About data multi-level security, the multi-level security data storage model and method are analyzed to realize the security isolation among different security-level data. And the information flow security policies are formulated to protect data interaction during of data processing procedure. The security of multi-source heterogeneous data storage are ensured in this project, at the same time the retrieval efficiency is improved and the secure interaction of multi-level security data is realized, which supports efficient security support for the information-based system in our control.