Additive Aggregate Function-based Data Privacy Protection Algorithm

Abstract

Data privacy protection is a key problem in the research and application of the internet of things that in wireless sensor networks has broad application prospects, such as agriculture environmental monitoring, healthcare, etc. For the core part of the internet of things, wireless sensor network, it is a very challenging task to provide effective privacy protection in the process of data transmission. In this paper, a new type of data privacy protection strategy based on the additive aggregation function is proposed (hereafter referred to as DPPA). On the one hand, applying the superposition property of the node data, the paper introduces the class aggregation protocol. On the other hand, taking advantage of the algebraic properties of the polynomials and the correlation properties of the superposed data, it can reduce the data of the header files of the data packages, and reduce the data size, while improving the privacy preservation. Simulation results show that DPPA can effectively protect data privacy, and get accurate data fusion results, while reducing the amount of data traffic.