Wireless sensor networks(WSNs)consist of a great deal of sensor nodes with limited power,computation,storage,sensing and communication capabilities.Data aggregation is a very important technique,which is designed to substantially reduce the communication overhead and energy expenditure of sensor node during the process of data collection in a WSNs.However,privacy-preservation is more challenging especially in data aggregation,where the aggregators need to perform some aggregation operations on sensing data it received.We present a state-of-the art survey of privacy-preserving data aggregation in WSNs.At first,we classify the existing privacy-preserving data aggregation schemes into different categories by the core privacy-preserving techniques used in each scheme.And then compare and contrast different algorithms on the basis of performance measures such as the privacy protection ability,communication consumption,power consumption and data accuracy etc.Furthermore,based on the existing work,we also discuss a number of open issues which may intrigue the interest of researchers for future work. Wireless sensor networks (WSNs) consist of a great deal of sensor nodes with limited power, computation, storage, sensing and communication capabilities. Data aggregation is a very important technique, which is designed to substantially reduce the communication overhead and energy expenditure of sensor node during the process of data collection in a WSNs.However, privacy-preservation is more challenging especially data aggregation, where the aggregators need to perform some aggregation operations on sensing data it received. We present a state-of-the-art asstrction of privacy -preserving data aggregation in WSNs. At first, we classify the existing privacy-preserving data aggregation schemes into different categories by the core privacy-preserving techniques used in each scheme. And then compare and contrast different algorithms on the basis of performance measures such as the privacy protection ability, communication consumption, power consumption and data accuracy etc. Futurertherm, based on the existing work, we also discuss a number of open issues which may intrigue the interest of researchers for future work.