TY - GEN
T1 - Privacy-Preserving Deep Learning for Erythemato-Squamous Disease Classification
AU - Wang, Yuhang
AU - Zhang, Hanlin
AU - Lin, Jie
AU - Kong, Fanyu
AU - Yu, Leyun
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Erythemato-squamous disease (ESD) is a benign skin condition with a broad spectrum of symptoms, creating diagnostic challenges for physicians. Numerous studies have suggested the use of deep learning for constructing classification models. However, the patient data utilized for model training and inference is highly confidential, and any breach could lead to severe implications. To address this issue, we introduce a deep learning framework that leverages secure multiparty computation to enable secure data sharing among entities while safeguarding privacy. Our framework, anchored on replicated secret sharing, enhances computational speed and curtails communication. We have conducted experiments to verify the performance of our framework, and the results demonstrate its accuracy and efficiency.
AB - Erythemato-squamous disease (ESD) is a benign skin condition with a broad spectrum of symptoms, creating diagnostic challenges for physicians. Numerous studies have suggested the use of deep learning for constructing classification models. However, the patient data utilized for model training and inference is highly confidential, and any breach could lead to severe implications. To address this issue, we introduce a deep learning framework that leverages secure multiparty computation to enable secure data sharing among entities while safeguarding privacy. Our framework, anchored on replicated secret sharing, enhances computational speed and curtails communication. We have conducted experiments to verify the performance of our framework, and the results demonstrate its accuracy and efficiency.
KW - classification of diseases
KW - deep learning
KW - erythemato-squamous disease
KW - privacy preservation
KW - secure multi-party computation
UR - https://www.scopus.com/pages/publications/85187346621
U2 - 10.1109/SWC57546.2023.10448834
DO - 10.1109/SWC57546.2023.10448834
M3 - 会议稿件
AN - SCOPUS:85187346621
T3 - Proceedings - 2023 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Autonomous and Trusted Vehicles, Scalable Computing and Communications, Digital Twin, Privacy Computing and Data Security, Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PCDS/Metaverse 2023
BT - Proceedings - 2023 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Autonomous and Trusted Vehicles, Scalable Computing and Communications, Digital Twin, Privacy Computing and Data Security, Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PCDS/Metaverse 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE Smart World Congress, SWC 2023
Y2 - 28 August 2023 through 31 August 2023
ER -