An Adaptive Grid and Incentive Mechanism for Personalized Differentially Private Location Data in the Local Setting

Algorithm 2

Hadamard count-min sketch LDP algorithm.

	Input: user’s location li, number of user n, confidence parameter , and user’s privacy specification ε1
	Output: user location count
(1)	Server calculates the number of grid
(2)	Server calculates
(3)	Server calculates m
(4)	Server generates a random matrix
(5)	Server initializes
(6)	Server initializes z and f
(7)	for each user uido
(8)	for each hash hjdo
(9)	server randomly generates k from {1, …, m}
(10)	server sends kth row to ui
(11)	ui returns to server
(12)	server adds to kth bit of
(13)	end for
(14)	end for
(15)	for each hash hjdo
(16)	for each hashed location do
(17)	server sets ‘s ith element of c to
(18)	end for
(19)	end for
(20)	return