In today's society,which has entered the era of big data,its mining work mainly relies on cloud computing platforms.However,the cloud computing environment is complex and ever-changing,and data security and privacy leakage issues are becoming increasingly prominent.A hybrid encryption scheme is proposed to address data security issues in cloud computing environments,u-sing different encryption methods based on data sensitivity levels.At the same time,a privacy preserving identifiable k-prototypes clustering algorithm was proposed,and the weight allocation of various numerical attributes was improved using information entropy to solve the privacy leakage problem in big data mining.The results show that the improved k-prototypes clustering algorithm has an NMI value of 0.284,an accuracy of 94.95%,an RI value of 0.935,and a running time of 924ms.Overall,this scheme ensures the secur-ity of data in the cloud environment while improving data encryption efficiency.
关键词
云计算/k-prototypes聚类算法/混合加密/敏感数据
Key words
cloud computing/K-prototypes clustering algorithm/mixed encryption/sensitive data
维普
万方数据