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Efficient sensitivity orient blockchain encryption for improved data security in cloud
Concurrent Engineering ( IF 2.118 ) Pub Date : 2021-04-12 , DOI: 10.1177/1063293x211008586
A Siva Kumar 1 , S Godfrey Winster 2 , R Ramesh 3
Affiliation  

Data security in the cloud has become a dominant topic being discussed in recent times as the security of data in the cloud has been focused on by several researchers. However, the data security was enforced at the attribute level, the adversaries are capable of learning the method of data encryption even there are access restrictions are enforced at an attribute level. To challenge the adversaries with more sophisticated security measures, an efficient real-time service-centric feature sensitivity analysis (RSFSA) model is proposed in this paper. The RSFSA model analyses the sensitivity of different features being accessed by any service and at multiple levels. At each level, the method checks the set of features being accessed and the number of features the user has access grant to compute the FLAG value for the user according to the profile given. Based on the value of FLAG, the user has been granted or denied service access. On the other side, the method maintains different encryption schemes and keys for each level of features. As the features are organized in multiple levels, the method maintains a set of schemes and keys for each level dedicative. Based on the service level and data, the method selects an encryption scheme and key to perform data encryption. According to that, the service access data has been encrypted at the attribute level with a specific scheme and key. Data encrypted has been uploaded to the blockchain and the method modifies the reference part of the chain to connect only the blocks to which the user has access. The chain given to the user would do not contain any reference from a specific block to which the user has no access. The proposed method improves the performance of data security and access restriction greatly.



中文翻译:

高效灵敏的面向区块链的加密技术可提高云中的数据安全性

云计算中的数据安全性已成为近来讨论的一个主要话题,因为云计算中的数据安全性已被一些研究人员所关注。但是,数据安全性是在属性级别实施的,即使在属性级别实施了访问限制,攻击者也可以学习数据加密的方法。为了以更复杂的安全措施挑战对手,本文提出了一种高效的实时以服务为中心的特征敏感度分析(RSFSA)模型。RSFSA模型分析了任何服务在多个级别访问的不同功能的敏感性。在每个级别,该方法检查要访问的功能集和用户有权访问的功能数量,以根据给定的配置文件为用户计算FLAG值。根据FLAG的值,已授予或拒绝该用户访问服务。另一方面,该方法为每个级别的功能维护不同的加密方案和密钥。由于功能是按多个级别组织的,因此该方法为每个级别的专用维护一组方案和键。基于服务级别和数据,该方法选择加密方案和密钥以执行数据加密。据此,已经使用特定的方案和密钥在属性级别对服务访问数据进行了加密。加密的数据已上传到区块链,并且该方法修改了链的参考部分,以仅连接用户有权访问的块。提供给用户的链将不包含来自用户无权访问的特定块的任何引用。所提出的方法大大提高了数据安全性和访问限制的性能。

更新日期:2021-04-13
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