A system for confidential training and inference for vertically partitioned dataset using secure multi-party computation /
- Title
- A system for confidential training and inference for vertically partitioned dataset using secure multi-party computation /
- Creator
- Shukla, Samiksha.
- Description
- Patent Number: 202241057386, Application: Kapil Tiwari.
The present invention applies to probabilistic inference employing secure multi-party computation (SMPC) methodologies including confidential training, inference, and model protection for vertically partitioned datasets. The proposed invention addresses privacy complexities of vertically partitioned data owners, model owners, and ML clients using confidential training, inference, and model protection (CoTraIn-VPD), a technique to boost data, model parameter, and client input privacy during ML inference without affecting accuracy or performance. - Date
- 2022-05-23
- Publisher
- Intellectual Property India
- Subject
- Computer Science
- Language
- English
- Type
- Patent
Files
Collection
Citation
Shukla, Samiksha., “A system for confidential training and inference for vertically partitioned dataset using secure multi-party computation /,” CHRIST (Deemed To Be University) Institutional Repository, accessed March 14, 2025, https://archives.christuniversity.in/items/show/2793.