Infinite Choices of Data Aggregations with Linear Number of Keys

Privacy-preserving data aggregation has long been a hot research issue. It is becoming increasingly important due to the widespread data collection for various analysis purposes. In this paper, we present a novel arithmetic protocol which computes sum and product of n individuals' input values without disclosing them, which is in turn used to develop an efficient accurate model to aggregate the data in a privacy-preserving manner. Unlike other approaches, our model initiates from an environment without secure communication channel but is robust to the eavesdrop attacks, and it does not rely on a trusted third party either. After the keys are prepared, only 1 communication round is needed to conduct each aggregation while some approaches require O(n) rounds. Notably, we allow any subset of n participants to privately conduct accurate data aggregation with only O(n) keys while similar works let every participant generate and hold O(2^n) keys or more.