基于秘密共享的轻量级隐私保护ViT推理框架OA北大核心CSTPCD

The ViT(vision transformer)inference framework,which was widely used in image processing,was found to have a risk of leaking user privacy data.However,existing privacy protection inference frameworks had problems such as low computational efficiency and high online communication volume.To address this issue,a highly efficient privacy protection inference framework SViT was proposed.Two edge servers collaborated to execute secure computing proto-cols based on secret sharing design,such as SSoftmax,SLayerNorm,SGeLU,etc.While maintaining the original frame-work structure of ViT-B/16,the problem of large inference overhead in privacy protection framework was solved.Theo-retical analysis and experiments show that compared to Crypton,SViT has improved computational efficiency by 2～6 times and online communication overhead by 4～14 times,respectively.