基于双混沌系统的大数据环境并行加密算法设计 

Design of Parallel Encryption Algorithm for Big Data Environment Based on Double Chaos System

摘要:

为了克服大数据在采用串行加密方式时具有的加密效率低的问题,设计了一种基于双混沌系统的大数据环境的并行加密算法；首先,设计了基于 Map-Reduce的大数据环境的并行加密模型；然后,引入了改进的Logistic映射和Tent映射构成双混沌系统,并设计了Map函数、Sort函数和Reduce函数实现并行加密,在Map函数中通过Logistic映射和Tent映射的不断迭代计算加密密钥或解密密钥,在Sort 函数对由Map函数输出的键值对进行排序并剔除重复的数据块,在Reduce函数中对加密后的密文数据块或解密后的明文数据块进一步合并构成输出数据；仿真实验表明:文中设计的基于双混沌系统的Map-Reduce并行加密模型能高效地进行数据加密或解密,能提高数据安全性和加密效率,具有较强的可行性。

Abstract:

In order to solve the problem of using the serial encryption having the problem of low efficiency,a parallel encryption algorithm is proposed based on double chaos system. Firstly,the parallel encryption model based on Map-Reduce for big data environment is designed. Then the parallel chaos system based on Logistic mapping and Tent mapping is designed,and the Map function,sort function and Reduce function are all designed,the Logistic mapping and Tent mapping is iterated to compute the encryption and decryption key in the Map function,and the data from Map function is merged to obtain the output data in the Reduce function,and the iteration initial value is computed and stored in the history data information for Logistic mapping and Tent mapping. The simulation experiment shows that the parallel model Map-Reduce model designed in this paper can achieve the encryption and decryption for big data,and it can improve the safety for data and enlarge the encryption efficiency with strong feasibility.