LEADER 01651nam 2200409 450 001 996574913703316 005 20231213215738.0 010 $a1-5044-7724-3 024 7 $a10.1109/IEEESTD.2021.9586768 035 $a(CKB)4100000012063351 035 $a(NjHacI)994100000012063351 035 $a(EXLCZ)994100000012063351 100 $a20231213d2021 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$a2830-2021 $eIEEE Standard for Technical Framework and Requirements of Trusted Execution Environment based Shared Machine Learning /$fInstitute of Electrical and Electronics Engineers 210 1$aNew York, NY, USA :$cIEEE,$d2021. 215 $a1 online resource (23 pages) 330 $aThe framework and architecture for machine learning in which a model is trained using encrypted data that has been aggregated from multiple sources and is processed by a trusted third party are defined in this standard. Functional components, workflows, security requirements, technical requirements, and protocols are specified in this standard. 606 $aMachine learning 606 $aDeep learning (Machine learning) 606 $aReinforcement learning 606 $aComputational learning theory 615 0$aMachine learning. 615 0$aDeep learning (Machine learning) 615 0$aReinforcement learning. 615 0$aComputational learning theory. 676 $a006.31 801 0$bNjHacI 801 1$bNjHacl 906 $aDOCUMENT 912 $a996574913703316 996 $a2830-2021$93651251 997 $aUNISA