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首页> 外文期刊>International Journal of Computer Science and Technology >An Efficient Secured Storage using Randomized Key Protocol in Cloud Computing
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An Efficient Secured Storage using Randomized Key Protocol in Cloud Computing

机译：云计算中使用随机密钥协议的高效安全存储

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Cloud computing opens new era in IT as it can give different flexible and adaptable IT services in a compensation as-you-go mold, where its clients can diminish the colossal capital interests in their very own IT foundation. In this theory, clients of cloud storage services never again physically keep up direct command over their data, which makes data security one of the real worries of utilizing cloud. Existing exploration work as of now enables data honesty to be checked without ownership of the genuine data record. Albeit a portion of the ongoing work based on BLS mark would already be able to help completely powerful data refreshes over settled size data squares, they just help refreshes with settled measured squares as essential unit, which we call coarse-grained refreshes. Accordingly, every little refresh will cause re-calculation and refreshing of the authenticator for a whole document square, which thusly causes higher storage and correspondence overheads. In this paper, we give a formal investigation to conceivable sorts of fine-grained data refreshes and propose a plan that can completely bolster approved inspecting and fine-grained refresh demands. Based on our plan, we likewise propose an upgrade that can drastically decrease correspondence overheads for checking little updates. Hypothetical examination and exploratory outcomes show that our plan can offer upgraded security and adaptability, as well as altogether bring down overhead for enormous data applications with countless little updates, for example, applications in online life and business exchanges.
机译：云计算开启了IT的新纪元，因为它可以按需补偿的方式提供不同的灵活性和适应性的IT服务，在这种形式下，其客户可以减少自己IT基础设施中的巨大资本利益。按照这种理论，云存储服务的客户再也不会从物理上保持对数据的直接控制，这使数据安全成为利用云的真正担忧之一。截至目前，现有的探索工作使您无需拥有真实数据记录就可以检查数据诚实性。尽管正在进行的基于BLS标记的工作的一部分已经可以在已确定大小的数据正方形上帮助完全强大的数据刷新，但它们仅以已确定测量的平方作为基本单位来帮助刷新，我们称之为粗粒度刷新。因此，每次小的刷新都会导致整个文档正方形的验证器的重新计算和刷新，从而导致更高的存储和通信开销。在本文中，我们对可能的各种细粒度数据刷新进行了正式调查，并提出了可以完全支持已批准的检查和细粒度刷新需求的计划。根据我们的计划，我们同样提出了一种升级，可以大大减少检查少量更新的通信开销。假设性检查和探索性结果表明，我们的计划可以提高安全性和适应性，并且可以减少大量数据应用程序的开销，而无需进行太多更新，例如在线生活和业务交流中的应用程序。

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