| Title | Machine Learning Method Based on Stream Homomorphic Encryption Computing |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Zhang, Y., Liu, Y., Chung, C.-L., Wei, Y.-C., Chen, C.-H. |
| Conference Name | 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan) |
| Date Published | sep |
| Keywords | \$k\$ nearest neighbors, computational resources, computational time, cryptography, Data analysis, Distributed databases, Elliptic curve cryptography, Encryption, Estimation, homomorphic encryption, human factors, k nearest neighbors, KNN, machine learning, Mathematical model, Metrics, mobile computing, mobile positioning, nearest neighbour methods, pubcrawl, Resiliency, Scalability, security, stream homomorphic encryption computing |
| Abstract | This study proposes a machine learning method based on stream homomorphic encryption computing for improving security and reducing computational time. A case study of mobile positioning based on k nearest neighbors ( kNN) is selected to evaluate the proposed method. The results showed the proposed method can save computational resources than others. |
| DOI | 10.1109/ICCE-Taiwan49838.2020.9258034 |
| Citation Key | zhang_machine_2020 |
Machine Learning Method Based on Stream Homomorphic Encryption Computing