基于多目标遗传算法的云数据安全存储方法  

Cloud Data Safe Placement Method Based on Multi-objective Genetic Algorithm

作　　者：吴超[1] 何利文[1] 唐澄澄 侯小宇 周睿 WU Chao;HE Li-wen;TANG Cheng-cheng;HOU Xiao-yu;ZHOU Rui(Nanjing University of Posts and Telecommunications,Nanjing 210003,China)

机构地区：[1]南京邮电大学,江苏南京210003

出　　处：《计算机技术与发展》2018年第11期135-141,共7页Computer Technology and Development

基　　金：2012年国家发改委信息安全专项(GJ215001);南京邮电大学引进人才科研启动基金资助项目(NY212012)

摘　　要：数据的存储安全和检索时间是云环境中数据存储的两个重要指标,而在确保存储数据安全的前提下最小化数据的检索时间是一个重要问题。从目标优化的角度来看,这是一个多目标优化问题。因此,提出了一种基于多目标遗传算法的云数据安全放置方法。该方法首先定义了一个与数据块和数据节点距离相关的安全水平,然后构建了一个最大化安全和最小化检索时间的约束多目标优化模型,最后采用遗传算法对提出的约束多目标问题进行求解,从而得到最优化的云数据安全放置策略。通过仿真实验可知,该策略在数据存储的安全性和数据的检索时间上具有很好的平衡,可以达到在满足数据存储安全的前提下最小化数据检索时间的目标。The retrieval time and storage security of data are two important indicators of data storage in cloud environment,and it is an important problem to minimize the retrieval time of data on the premise of ensuring the security of storage data.From the view of target optimization,this is a multi-objective optimization problem.Therefore,we propose a secure placement method of cloud data based on multi-objective genetic algorithm.It defines a security level associated with the data block and the data node distance,and then builds a constrained multi-objective optimization model with maximum safety and minimum retrieval time.Finally by genetic algorithm the constrained multi-objective problem is solved in order to get the optimal placement strategy of cloud data security.According to simulation,it has a great balance between safety of data storage and data retrieval time,achieving the goal of minimizing the data retrieval time on the premise of ensuring the data storage security.

关 键 词：遗传算法 多目标优化 数据安全 数据检索 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]