同态加密, 智能信息化数据库, 隐私保护, 主成分分析, K-means 聚类

To solve the problem of data leakage in intelligent information databases, a privacy protection method for intelligent information databases based on homomorphic encryption is proposed. Firstly, principal component analysis is used to extract the features of data in intelligent information database. Secondly, the K-means clustering algorithm is used to classify database data, in order to improve the efficiency of subsequent data encryption. Finally, the elliptic curve homomorphic encryption algorithm is adopted to encrypt the clustered database data, achieving privacy information protection of the database. The experimental results show that the total entropy value is close to 0, and the maximum entropy value does not exceed 0. 01. And the encrypted data distribution is irregular, and the distance between the data is relatively consistent. The probability of leakage remains within 1% , and the overall increase is relatively small. This proves the practicality of the proposed method in protecting database privacy.