Improving the Confidential Data Totalization

With a rapid spread of the cloud computing, confidential data totalization technologies are becoming more important. In 2011, Ushida et al. proposed a confidential data totalization technique based on the value distortion, in which each data in a formulaic corss-tabulation table is randomized by a random data shared in a pre-provided random data table, and the cloud server is able to totalize the data by summing randomized data since the sum of the randomized table data is known to the server. So the cloud server does not require any specific functions for totalizing randomized data and no information is leaked to the cloud server. However, there are tow problems. The first problem is data leakage from randomized table data if the same random table is used twice or more. The second problem is the difficulty of appending new rows or columns to the random data table without reproviding them to the users. This paper introduces solutions for these problems: a table updating method for the random table and and a table extending method for the random table without any re-provisions. With the proposed solutions, the cost of the the secure table data analysis method for the update and the extension can be reduced extremely.