云环境中海量数据的并行分组密码体制研究  

Parallel Processing of Block Cipher for Massive Data in Cloud Computing

作　　者：师金钢[1] 郑艳[2] 孙焕良[1] 栾方军[1] 

机构地区：[1]沈阳建筑大学信息与控制工程学院,沈阳110168 [2]沈阳东方钛业股份有限公司,沈阳110168

出　　处：《计算机科学与探索》2014年第2期161-170,共10页Journal of Frontiers of Computer Science and Technology

基　　金：国家自然科学基金 Grant No.61070024;住房和城乡建设部项目 Grant No.2012k830~~

摘　　要：云计算环境中,飞速增长的海量数据的安全性越来越受到关注,分组密码算法是保证海量数据安全性的一个有效手段,但面对超大规模的数据量其效率是一个备受关注的问题。提出了一种基于MapReduce架构的并行分组密码机制,能够使标准的分组密码算法应用于大规模的集群环境中,通过并行化来提高海量数据加密与解密的执行效率,并设计了常用的几种并行工作模式。实验证明,提出的算法具有良好的可扩展性和高效的执行性能,能够适用于云计算环境中海量数据的安全保密,为进一步的研究工作奠定了基础。In the cloud computing, the security of massive data is paid more and more attention. And the block cipher algorithm is an effective means to ensure that the massive data are secure. But the efficiency is a significant problem for the massive amount of data. This paper presents a parallel block cipher mechanism based on the MapReduce architecture that enables a standard block cipher algorithm to be applied to a large-scale cluster environment. Then this paper improves the implementation efficiency of the massive data encryption and decryption by parallelization, and designs several common parallel working modes. Finally, the experiments show that the proposed algorithm has good scalability and efficient performance. So it can not only be adapted to the security of massive data in the cloud computing environment, but also lay the foundation for further research work.

关 键 词：分组密码 工作模式 并行计算 云计算 

分 类 号：TP393.1[自动化与计算机技术—计算机应用技术]