JR/T 0196-2020 in English
VALIDSecure multi-party computation financial application technical specification
- Issued on:2020-11-24
- Implemented on:2020-11-24
- File Format:PDF
- Delivery:Via email within 1~3 business days
$262.00
| Standard No: | JR/T 0196-2020 |
| Document status: | VALID |
| Title in English: | Secure multi-party computation financial application technical specification |
| Title in Chinese: | 多方安全计算金融应用技术规范 |
| Language: | English |
| File Format: | Electronic (PDF) |
| Delivery: | Via email within 1~3 business days |
| Issued on: | 2020-11-24 |
| Implemented on: | 2020-11-24 |
| ICS Classification: | 35.240.40-IT applications in banking |
| Chinese Classification: | A11-Finance and Insurance |
| Professional Classification: | JR-Finance |
| Related Topics: | Applied technology
finance biocomputing applications Density meter with many applications financial calculation joint modeling Metallography with many applications JR/t Multi-party secure computing financial application technology Secure multi-party computing technology "Computing Application Standards" jr/t 0118 jr/t 0196-2020 Multi-party secure computing application technology |
Introduction
Interpretation of the core content of the standard
| Technical dimensions | Basic requirements | Security requirements | Performance indicators |
|---|---|---|---|
| Data input | Support 6 types of data source conversion | Input factors are irreversible | Real number multiplication ≤1000ms |
| Algorithm support | Covering 15+ machine learning algorithms | Model parameter protection | TPS≥500 times/second |
| Computing protocol | Semi-honest/malicious model | Safety parameter k≥112 | Precision≥26 bits |
Analysis of key technical requirements
1. Role system of participants
The standard clearly defines 6 types of participants: task initiator, scheduler, algorithm provider, data provider, calculator and result user. The calculator must be deployed across management domains, and a single entity cannot concurrently serve as multiple computing nodes.
2. Security model classification
The standard requires that the statistical security parameter l ≥ 30 (2-30 indistinguishability) and the computational security parameter k ≥ 112 (cracking complexity 2112) should reach financial-level security strength.
Typical application implementation suggestions
1. Biometric recognition
Process facial feature data through secret sharing technology to achieve:
- Registration stage: original image→calculation factor conversion
- Verification stage: terminal directly uploads calculation factors
- Avoid plaintext transmission and storage of facial data
2. Joint risk control modeling
Financial institutions adopt homomorphic encryption + gradient descent solutions:
- Local data of each institution remains encrypted
- Model parameters are exchanged through the MPC protocol
- Final model accuracy requirement ≥ 32 effective bits
Standard evolution background
This standard fills the gap in the application of MPC technology in the financial field and complements JR/T 0171 "Technical Specifications for the Protection of Personal Financial Information". The key technical indicators refer to the ISO/IEC 29101 privacy architecture framework and are combined with the actual needs of my country's financial industry:
- 2018: The first batch of banks pilot MPC joint anti-fraud
- 2019: Implementation of the national standard for cloud computing (GB/T 32400)
- 2020: This standard is released to regulate the application of MPC in the financial industry

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