Journal of Frontiers of Computer Science and Technology ›› 2014, Vol. 8 ›› Issue (2): 161-170.DOI: 10.3778/j.issn.1673-9418.1305054

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Parallel Processing of Block Cipher for Massive Data in Cloud Computing

SHI Jingang1+, ZHENG Yan2, SUN Huanliang1, LUAN Fangjun1   

  1. 1. School of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China
    2. Shenyang Orient Titanium Industry Co. Ltd, Shenyang 110168, China
  • Online:2014-02-01 Published:2014-01-26


师金钢1+,郑  艳2,孙焕良1,栾方军1   

  1. 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

Abstract: 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.

Key words: block cipher, mode of operation, parallel computing, MapReduce, cloud computing

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。

关键词: 分组密码, 工作模式, 并行计算, MapReduce, 云计算