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Privacy Based Preservation in Multi Cloud Environment Using Attribute Level Trusted Access Measure Technique

机译:使用属性级别可信访问测量技术基于多云环境的隐私保存

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摘要

The Portent of data security in cloud setting is well studied. There are number of approaches has been discussed for the data security in multi cloud environments. The previous methods suffer to achieve higher performance in data security and privacy preservation. To improve the performance, an attribute level trusted access measure is presented. The method classifies the user data into several classes and for each class of attributes different access restriction has been enforced. The access between different cloud has been restricted based on the attribute level trusted access measure (ALTAM). The ALTAM measure for each request has been estimated based on the depth of privacy has been accessed by the request and the number of data values the user has access in the cloud and outside the cloud. Based on all these the method estimates the trust measure. According to the trust measure, the method restrict the access of data in multi cloud environments. The method produces efficient result in access restriction and privacy preservation.
机译:云环境下数据安全的先兆已经得到了很好的研究。对于多云环境中的数据安全,已经讨论了许多方法。以前的方法难以在数据安全和隐私保护方面实现更高的性能。为了提高性能,提出了一种属性级可信访问度量。该方法将用户数据分为若干类,并对每一类属性实施了不同的访问限制。基于属性级可信访问度量(ALTAM),不同云之间的访问受到限制。每个请求的ALTAM度量是根据请求访问的隐私深度以及用户在云中和云外访问的数据值的数量来估计的。基于所有这些,该方法估计信任度量。根据信任度量,该方法限制了多云环境下的数据访问。该方法在访问限制和隐私保护方面产生了有效的效果。

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