Review of privacy computing techniques for multi-party data fusion analysis by LIU Shenglong, HUANG Xiuli, JIANG Yiwen, JIANG Jiawei, TIAN Yuechi, ZHOU Zejun, NIU Ben

“…This work focused on the needs of multi-party privacy computing for cross-system exchanges in ubiquitous sharing environments, taking the security sharing and controlled dissemination of private data in multi-party data fusion applications as the starting point, and provided reviews of existing relevant work from the perspectives of multi-party privacy computing, multi-party privacy information sharing control, and multi-party data collaborative secure computing. …”
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Double layer federated security learning architecture for artificial intelligence of things by ZHENG Chengbo, YAN Haonan, FU Caili, ZHANG Dong, LI Hui, WANG Bin

“…The entire security learning system was divided into a two-level architecture of bottom and top layers. …”
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