Table 7.

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

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

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

The attribute values followed non-uniform distribution