【摘要】 为满足用户隐私数据传输的安全性需求，提出一种同态加密下用户隐私数据传输安全保护方法.首先，通过特征空间重组技术进行数据重构，利用语义相关性融合方法在捕获用户隐私数据特征的同时进行自适应调度，并对捕获的特征量进行模糊聚类，确定用户隐私数据属性；其次，结合用户隐私数据属性，采用同态加密算法和深度学习相结合的方法对用户隐私数据进行点对点加密传输，最终实现用户隐私数据传输安全保护.仿真实验结果表明，该方法的数据加密效果较好，通信开销较低，可以更好地确保用户隐私数据传输的安全性和可靠性.更多还原

【Abstract】 In order to meet the security requirements of user privacy data transmission, we proposed a security protection method for user privacy data transmission under homomorphic encryption. Firstly, by using feature space recombination technology for data reconstruction, semantic correlation fusion method was used to capture user privacy data features while adaptively scheduling, and fuzzy clustering was performed on the captured feature quantities to determine user privacy data attributes. Secondly, combining the attributes of user privacy data, a combination method of homomorphic encryption algorithms and deep learning was used to encrypt and transmit user privacy data point-to-point, ultimately achieving secure protection of user privacy data transmission. The simulation experiment results show that the proposed method has good data encryption effect, low communication overhead, and can better ensure the security and reliability of user privacy data transmission.更多还原