Module - Privacy Preserving Machine Learning

by Daniel Huynh

Table of Contents

Privacy Preserving Machine Learning

0:00 Presentation
2:50 Context and cloud data threads
5:15 Confidential Computing (CC)
7:12 Intel SGX
8:40 Enclave
12:19 Azure Attestation Service
13:25 Use cases
14:50 Abdstraction layers for enclaves
15:57 Open enclave SDK
16:27 Lightweight OS + Demo (Graphene SGX)
23:44 Multi-party machine learning
26:50 Q&A
33:26 Homomorphic Encryption (HE)
37:20 CKKS encoder
41:29 Homomorphic Encryption high-level view
42:24 Homomorphic Encryption in practice
45:17 Demo with TenSEAL
50:25 Demo Homomorphic Random Forests
1:01:38 to go beyond
1:02:28 Secure Multi-Party Computing (MPC)
1:07:58 Conclusion

Slides and code

• slides

• Cryptotree: Homomorphic Random Forests

to go beyond

• Homomorphic Encryption