Gimme That Model!: A Trusted ML Model Trading Protocol
arXiv:2003.00610v24 citations
Originality Synthesis-oriented
AI Analysis
This addresses the need for trusted model exchange in ML applications, though it appears incremental as it builds on existing cryptographic techniques.
The paper tackles the problem of secure machine learning model trading by proposing a homomorphic encryption-based protocol, with suggested improvements to enhance transaction efficiency and security.
We propose a HE-based protocol for trading ML models and describe possible improvements to the protocol to make the overall transaction more efficient and secure.