A Privacy Preserving Scheme for Nearest Neighbor Query

. 2018 Jul 27;18(8):2440. doi: 10.3390/s18082440

Algorithm 1 RNR algorithm

Require:

M_{q}

;

q_{r e a l}

;
Ensure:
k noise data sets

N_{1}, \dots, N_{k}

;

1:
$S N I P P E T S$ = searchTree( $q_{r e a l}$ );
2:
if $s i z e o f (S N I P P E T S) \geq k$ then
3:
for each snippet in $S N I P P E T S$ do
4:
if vertex number of $s n i p p e t_{i}$ is larger than vertex number of real data then
5:
$N o i s e S e t_{i} = random_vertex (s n i p p e t_{i})$ ;
6:
end if
7:
end for
8:
randomly choose $N_{1}, \dots, N_{k}$ from $N i o s e S e t$ ;
9:
return $N_{1}, \dots, N_{k}$ ;
10:
else
11:
reduce q and repeat from line 1;
12:
end if