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Table 7 The lowest MSE for the existing method and the enhancements, tested on synthetic 20-dimensional dataset having 50,000 records

From: Sarve: synthetic data and local differential privacy for private frequency estimation

Method

ε = ln(2)

ε = ln(3)

ε = ln(4)

ε = ln(5)

ε = ln(6)

ε = ln(7)

RS + FD[ADP]

0.000105

6.24E−05

4.30E−05

3.35E−05

2.77E−05

2.41E−05

RAPPOR

0.000155

0.000121

9.77E−05

8.32E−05

7.35E−05

6.61E−05

Hadamard response

0.000159

7.82E−05

5.37E−05

4.32E−05

3.57E−05

3.27E−05

Sarve

0.000113

6.46E−05

4.51E−05

3.39E−05

2.77E−05

2.50E−05

Method

ε = 2

ε = 3

ε = 4

ε = 5

ε = 6

ε = 7

RS + FD[ADP]

2.35E−05

8.77E−06

4.36E−06

2.69E−06

2.17E−06

1.78E−06

RAPPOR

6.64E−05

3.93E−05

2.24E−05

1.31E−05

8.06E−06

5.27E−06

Hadamard response

3.29E−05

2.12E−05

1.90E−05

1.77E−05

1.58E−05

1.75E−05

Sarve

2.27E−05

8.76E−06

4.33E−06

2.55E−06

1.96E−06

1.72E−06

  1. The values in bold indicate privacy conditions when Sarve performed better than adaptive RS+FD and resulted in lower MSE between real and post-privatization estimated frequencies
  2. The attribute values followed non-uniform distribution