Protecting Classification Privacy Data Aggregation in Wireless Sensor Networks

Abstract

As broad deployed of wireless sensor networks, privacy concerns have emerged as the main obstacle to success. When wireless sensor networks are used in everyday life, the privacy about monitored object' sensitive data becomes an important issue. Consequently, providing efficient data aggregation privacy protection is desirable. However, the existing technique is always energy exhausting, and does not consider different privacy levels of data aggregation. In this paper, DADPP (Data Aggregation Different Privacy-Levels Protection) is proposed to deal with data aggregation privacy protection. DADPP offers different levels of data aggregation privacy based on different node-numbers for pretreating data. According to desired privacy level, all nodes within the same cluster are partitioned into many groups, any group including node- numbers belong to the same privacy level. Data are pretreated only in the same group. Compared with the existing technique, DADPP has lower energy costs while ensuring expected privacy level.