The powerful resource advantage of the cloud provides a suitable computing environment for data processing. By transferring local computing to the cloud, the efficiency of data processing can be improved. However, the open cloud environment has defects in data privacy-preserving. In order to strengthen the protection of data privacy and ensure the security of multi-party interaction, we propose a privacy-preserving multi-party computing scheme for K-means clustering (PPMCK). PPMCK can preserve data privacy in the cloud and in the local side for each party from multi-party computing. In addition, PPMCK uses homomorphic encryption to protect data privacy. To support the division operation and ciphertext value size comparison with which homomorphic encryption cannot handle, the corresponding measurements are adopted, which make homomorphic encryption work smoothly. The experimental results demonstrate that PPMCK is effective in both data processing and privacy-preserving.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence