Source · Tier A · Peer-reviewedSource · Zero-Knowledge Proofs of Training for Deep Neural Networks
Zero-Knowledge Proofs of Training for Deep Neural Networks
K. Abbaszadeh, C. Pappas, J. Katz, D. Papadopoulos. 2024. 2024 ACM SIGSAC Conference on Computer and Communications Security (CCS 2024), pp. 4316-4330.
| Original | https://eprint.iacr.org/2024/162 |
|---|---|
| DOI | 10.1145/3658644.3670316 |
| Version | Read the IACR ePrint version (last revised 22 July 2024). Venue and DOI from the HKUST research portal record. On 2026-10-08 the abstract and indexed paper excerpts were re-read; direct PDF downloads were not reachable. On 2026-10-13 the ePrint abstract was re-read; the PDF was behind a browser challenge and the ACM page returned 403. |
| Accessed | 2026-10-20 |
| Note | Describes the Kaizen zkPoT system. |
Cited by
- Zero-knowledge proofs of training constraintsMechanism
- KaizenImplementation
- A training run stayed within declared limitsClaim