TY - GEN
T1 - Feature Engineering Framework based on Secure Multi-Party Computation in Federated Learning
AU - Sun, Litong
AU - Du, Runmeng
AU - He, Daojing
AU - Zhu, Shanshan
AU - Wang, Rui
AU - Chan, Sammy
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2022
Y1 - 2022
N2 - Data and features often determine the upper limit of results, so that feature engineering is an important stage of federated learning. The existing research schemes all carry out feature engineering based on publicly sharing data. One is plaintext data sharing, the other is ciphertext data sharing, but both types of sharing bring security and efficiency problems. To address these challenges, we propose a feature engineering framework based on Secure Multi-party Computation, which supports multi-party participation in feature engineering and confines feature data locally to ensure data security. Moreover, the computational efficiency of the core algorithm of the framework is also improved compared with the existing methods.
AB - Data and features often determine the upper limit of results, so that feature engineering is an important stage of federated learning. The existing research schemes all carry out feature engineering based on publicly sharing data. One is plaintext data sharing, the other is ciphertext data sharing, but both types of sharing bring security and efficiency problems. To address these challenges, we propose a feature engineering framework based on Secure Multi-party Computation, which supports multi-party participation in feature engineering and confines feature data locally to ensure data security. Moreover, the computational efficiency of the core algorithm of the framework is also improved compared with the existing methods.
KW - Feature Engineering
KW - Federated Learning
KW - Privacy Protection
KW - Secure Multi-party Computation
UR - https://www.scopus.com/pages/publications/85132443676
U2 - 10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00088
DO - 10.1109/HPCC-DSS-SmartCity-DependSys53884.2021.00088
M3 - 会议稿件
AN - SCOPUS:85132443676
T3 - 2021 IEEE 23rd International Conference on High Performance Computing and Communications, 7th International Conference on Data Science and Systems, 19th International Conference on Smart City and 7th International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021
SP - 487
EP - 494
BT - 2021 IEEE 23rd International Conference on High Performance Computing and Communications, 7th International Conference on Data Science and Systems, 19th International Conference on Smart City and 7th International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021
Y2 - 20 December 2021 through 22 December 2021
ER -