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JR/T 0196-2020 in English

JR/T 0196-2020 in English

VALID

Secure 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
Price(USD): $270.00
$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

Case: In the joint credit investigation scenario, when the semi-honest model is adopted, all participating institutions are required to sign a compliance agreement; if there is a risk of malicious institutions, the malicious attack model needs to be enabled and the dishonesty threshold ≥ 3.

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:

  1. Local data of each institution remains encrypted
  2. Model parameters are exchanged through the MPC protocol
  3. 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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