Privacy-preserving parallel kNN classification algorithm using index-based filtering in cloud computing.

ABSTRACT: With the development of cloud computing, interest in database outsourcing has recently increased. In cloud computing, it is necessary to protect the sensitive information of data owners and authorized users. For this, data mining techniques over encrypted data have been studied to protect the original database, user queries and data access patterns. The typical data mining technique is kNN classification which is widely used for data analysis and artificial intelligence. However, existing works do not provide a sufficient level of efficiency for a large amount of encrypted data. To solve this problem, in this paper, we propose a privacy-preserving parallel kNN classification algorithm. To reduce the computation cost for encryption, we propose an improved secure protocol by using an encrypt

SUBMITTER: Kim YK 

PROVIDER: S-EPMC9070920 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature