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Privacy preserving of intermediate dataset using hybridisation of oppositional gravitational search algorithm and elliptic curve cryptography

机译:对立重力搜索算法和椭圆曲线密码学混合保护中间数据集的隐私

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摘要

Distributed computing gives the gigantic capacity ability to the clients to send their applications without any infrastructure investment. Based on the application lot of intermediate dataset will be created. To protecting these intermediate dataset is a challenging task. Moreover, encrypting all dataset is a time and cost consuming. To overcome the problem, in this paper we proposed a privacy preserving of intermediate dataset using a combination of oppositional gravitational search algorithm and elliptic curve cryptography (OGSA + ECC). Initially, we split the dataset into a number of the intermediate datasets, then, we choose the node corresponding intermediate dataset from the cloud using an oppositional gravitational search algorithm (OGSA). After that, we choose the sensitive data from the dataset using the information gain measure to minimise the processing time and cost. Then, using the ECC algorithm the sensitive data is encrypted and in the cloud the secure data are stored. The experimentation is carried out in terms of encryption time and memory use.
机译:分布式计算使客户无需任何基础设施投资即可拥有巨大的能力来发送其应用程序。根据应用程序将创建大量中间数据集。保护这些中间数据集是一项艰巨的任务。而且,对所有数据集进行加密既费时又费钱。为了解决这个问题,在本文中,我们提出了使用对立重力搜索算法和椭圆曲线密码学(OGSA + ECC)组合的中间数据集的隐私保护方法。最初,我们将数据集拆分为多个中间数据集,然后,使用对立重力搜索算法(OGSA)从云中选择节点对应的中间数据集。之后,我们使用信息增益度量从数据集中选择敏感数据,以最大程度地减少处理时间和成本。然后,使用ECC算法对敏感数据进行加密,并将安全数据存储在云中。实验是根据加密时间和内存使用情况进行的。

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