Re-ADP: Real-Time Data Aggregation with Adaptive -Event Differential Privacy for Fog Computing

Algorithm 1

A real-time stream data aggregation framework with adaptive -event differential privacy (Re-ADP).

Input: The raw data database at the th time stamp

Output: The aggregation secure statistics

  Find out the optimal number of sampling points

  Find out sets of sampling sensors at the current time stamp

  Obtain the grouping strategy via smart grouping

  Allocate the budget for all sampling sensors

  Add Laplacian noise to group with allocated budget at the perturbation mechanism

  Report the aggregated secure statistics that is filtered by Kalman filtering.

  Update the sampling interval by adaptive sampling