Statistical analysis for the key representation database and the original database

A statistical database (SDB) is a database that allows its users to retrieve aggregate statistics (such as sum, average, count, etc) on subsets of records, and data in individual records should be remained secret. The key representation auditing scheme (KRAS) is proposed to protect the privacy of online and dynamic SDBs. The core idea is to convert the original database into key representation database (KRDB), also this scheme involves converting each new user query from string representation into key representation query (KRQ), and stores it in the Audit Query table (AQ table). Three audit stages are proposed to repel the attacks of the snooper to the confidentiality of the individuals. In this paper, we provide statistical analysis to compare between the means and variances of the original database and the KRDB populations. We test the null hypothesis, that there will be no significant difference between the two populations´ means/variances, against the alternative hypothesis, that there will be a significant difference between the two populations´ means/variances. The results of the tests showed that the differences are statistically significant.