远程不可信存储的数据完整性巡检算法研究

Research on Verification Algorithm of Data Integrity Inspecting in Remote Untrusted Storage

数据所有者把自己的数据存储在远程存储空间正成为一种非常有前景的数据服务模式.这种数据存储因数据所有者失去对数据的直接控制,而面临着不可信第三方存储服务提供商(Storage Service Provider,SSP)造成数据丢失的潜在威胁.目前普遍采用基于同态技术的数据完整性校验算法,但现有的算法中忽略了数据检测时数据大小、数据重要性等数据自身因素对检测效率的影响.提出一种基于伪随机函数和同态BLS短签名的混合校验算法,结合被校验数据的大小和重要性等因素,在权衡检测效率和校验安全性下采用概率循环抽样检测方式执行数据巡检.理论分析和模拟测试结果表明,算法在区分不同重要性的数据及数据大小的条件下,提高了数据巡检时的检测效率.

Cloud storage service, which allows data owners store their data at remote servers, has been becoming a significantly promis- ing data service mode. However,due to data owners losing direct control of their data,it is subject to the potential threat of data loss or corruption brought by the untrusted third-party storage service provider （ SSP }. Currently, most of data integrity verification algorithms are based on the homomorphic verification technology, but they ignore some factors such as the size and importance of checked data, which have a significant impact on the verification efficiency in data inspecting process. In this paper,we propose a mixed verification algorithm based on pseudo-random function and homomorphic BLS short signature technology. The algorithm combines with the size and importance of checked data and utilizes the looping probability sampling to execute inspecting verification to assure the data in- specting efficiency and verification security. Theoretical analysis and simulation results show that the algorithm improves the verifica- tion efficiency in the data inspecting while the importance rank of data and the data size are differentiated.