Research Article

A Clustering -Anonymity Privacy-Preserving Method for Wearable IoT Devices

Algorithm 1

Clustering -anonymity.
INPUT:
the data table need to be published: PT;
the anonymous parameter: ;
Quasi-identifiers: ;
OUTPUT:
the data table GT satisfies -anonymity;
the list of quasi-identifiers: LF;
the list of records with similar quasi-identifiers: F;
the list LO as the list of L;
Repeat
Calculate between and other records ;
(3)Cluster the nearest records with ;
(4)Remove these records form LF, and add these records to L;
(5)Select the farthest records from to be the new core;
(6)Add L to LO, then clear L.
(7)until  
(8)The remained records in LF are assigned to the nearest cluster in LO;
(9)Unify each cluster in LO by Generalizing;
(10)Create GT, QI from LO, and create SD from PT;
(11)return GT