Research on a hybrid encryption sensitive data protection scheme based on k-prototypes clustering algorithm
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.
cloud computingK-prototypes clustering algorithmmixed encryptionsensitive data
万方数据
维普
