基于服务器管理算法的不可信云中数据一致性和存储安全
Secured Data Consistency and Storage Way in Untrusted Cloud using Server Management Algorithm
摘要：
这是非常具有挑战性的一部分，以保持安全的所有所需的数据，需要在许多应用程序中的用户在云中。将我们的数据存储在云中可能并不完全可信。由于客户端没有所有存储数据的副本，因此必须依赖云服务提供商。但是动态数据操作、Read-Solomon和验证令牌构造方法并没有告诉我们云上数据添加前后服务器分配空间的总存储容量。因此，我们必须引入一个新的建议系统的有效的存储测量和空间比较算法与时间管理测量总分配的存储区域之前和之后的数据插入云。因此，通过使用我们提出的方案，之前和之后的存储数据的值或权重是由客户端在云存储区域中的指定时间内准确测量的。在这里我们还提出了服务器故障情况下的多服务器恢复点。当服务器发生故障时，通过该方案可以在云服务器中自动恢复数据。我们提出的方案有效地检查空间的外包数据，以保持完整性。在这里，TPA不一定具有审计用户数据的授权。
英文摘要：
It is very challenging part to keep safely all required data that are needed in many applications for user in cloud. Storing our data in cloud may not be fully trustworthy. Since client doesn't have copy of all stored data, he has to depend on Cloud Service Provider. But dynamic data operations, Read-Solomon and verification token construction methods don't tell us about total storage capacity of server allocated space before and after the data addition in cloud. So we have to introduce a new proposed system of efficient storage measurement and space comparison algorithm with time management for measuring the total allocated storage area before and after the data insertion in cloud. So by using our proposed scheme, the value or weight of stored data before and after is measured by client with specified time in cloud storage area with accuracy. And here we also have proposed the multi-server restore point in server failure condition. If there occurs any server failure, by using this scheme the data can be recovered automatically in cloud server. Our proposed scheme efficiently checks space for the in-outsourced data to maintain integrity. Here the TPA necessarily doesn't have the delegation to audit user's data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
