科研成果详情

为了改进存储机制,以提供一个通用的隐私保护服务,提出了一种基于边缘的数据保护模型,将无线传感器网络收集的原始数据交由边缘服务器,并利用隐私计算算法进行差分处理.少量核心数据存储在边缘服务器和本地服务器上,其他数据传输到云端存储.基于该模型,即使存储在云中的数据被泄露,原始数据也无法被恢复,数据的隐私权得以保证;采用差分存储方法,减少了发送到云端的数据,降低了通信成本和存储成本.理论分析和大量实验结果证实了该方法有效. 

To improve the storage mechanism to provide a general privacy protection service, a data protection model based on edge computing is presented. The original data collected by wireless sensor networks is differentiated by privacy computing algorithm on edge servers. A small amount of core data is stored on edge servers and local servers, while other data is transferred to the cloud for storage. Based on the model, even if the data stored in the cloud is leaked, the original data cannot be recovered, so the privacy of the data can be ensured. The differential storage method reduces the data sent to the cloud and decreases the communication cost and storage cost. Both theoretical analyses and a large number of experiments have proved the effectiveness of the proposed method.