多路复用大型云动态数据完整性检测方法

Method of Multiplex Large Cloud Dynamic Data Integrity Detection

对大型云动态数据的完整性检测可以避免云用户存储在其中数据被篡改或删除。传统方法中,采用代数结构标签加密方法进行数据完整性检测,不能保证足够的置信度,性能不好。在云储存环境下,提出一种基于可信第三方判定和动态标签信息更新的多路复用大型云动态数据完整性检测方法。假设被处理云采集数据的是可分类的,引入了一个管理因子,得到多路复用标签信息,基于可信第三方判定和动态标签信息更新进行,进行对用户存在云存储服务器上的文件块被篡改或删掉的判定,由此实现一次数据完整性验证,提高大型云动态数据检测的准确性。仿真结果表明,该算法具有较好的多路复用大型云动态数据完整性检测性能,系统使用率提高,计算开销较少,检测准确性提高。

The integrity detection of dynamic data of large clouds can avoid the cloud user storage in which data was modi?fied or deleted. In the traditional method, encryption method for data integrity detection using the algebraic structure of la?bel, it cannot guarantee sufficient confidence, the performance is not good. In the cloud storage environment, proposes a multiplexing large cloud dynamic data integrity detection method of trusted third party determination and dynamic label based on information update. The hypothesis is processing cloud data acquisition can be classified, introduced a manage?ment factor, be multiplexed label information, a trusted third party determination and the dynamic tag information based on user updates, there found cloud storage of files on the server block was manipulated or deleted, thereby realizing a data in?tegrity verification to improve the accuracy of dynamic data, large cloud detection. The simulation results show that, the al?gorithm has the multiplex large cloud dynamic data integrity better detection performance, less computation cost, improve detection accuracy.