SAGMA: Secure Aggregation Grouped by Multiple Attributes
Timon Hackenjos, Florian Hahn, Florian Kerschbaum
Abstract
Encryption can protect data in outsourced databases -- in the cloud -- while still enabling query processing over the encrypted data. However, the processing leaks information about the data specific to the type of query, e.g., aggregation queries. Aggregation over user-defined groups using SQL's GROUP BY clause is extensively used in data analytics, e.g., to calculate the total number of visitors each month or the average salary in each department. The information leaked, e.g., the access pattern to a group, may reveal the group's frequency enabling simple, yet detrimental leakage-abuse attacks. In this work we present SAGMA -- an encryption scheme for performing secure aggregation grouped by multiple attributes. The querier can choose any combination of one or multiple attributes in the GROUP BY clause among the set of all grouping attributes. The encryption scheme only stores semantically secure ciphertexts at the cloud and query processing hides the access pattern, i.e., the frequency of each group. We implemented our scheme and our evaluation results underpin its practical feasibility.