A novel privacy-preserving data gathering scheme in WSN based on compressive sensing and embedding

As wireless sensor networks (WSN) is resource-constrained and vulnerable, a secure data gathering scheme is desirable. Compressive data gathering based on compressive sensing (CS) embodies its superiority to reduce the communication energy and prolong the network life. However, Compressive data gathering is prone to attack due to the open environment. In this paper, we propose a novel compressive data gathering scheme based on embedding mechanism. To implement privacy-preserving, the selected nodes determined by the sink embed the blinding factors, while the unselected nodes exploit the confusion factors. This scheme ensures low communication overhead at senor nodes and no aggravating complexity at the sink. Extensive evaluations and comparisons validate the effectiveness of our design.