https://github.com/alan-turing-institute/dpht
Differentially Private Health Tokens (for Estimating COVID-19 Risk)
Science Score: 33.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: arxiv.org -
✓Committers with academic emails
1 of 3 committers (33.3%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.4%) to scientific vocabulary
Repository
Differentially Private Health Tokens (for Estimating COVID-19 Risk)
Basic Info
- Host: GitHub
- Owner: alan-turing-institute
- License: mit
- Language: Python
- Default Branch: master
- Size: 127 KB
Statistics
- Stars: 1
- Watchers: 7
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Differentially Private Health Tokens (DPHT)
Paper
The latest DPHT paper can be found at arXiv. The authors welcome feedback and may be contacted by email using the details in the paper or by clicking the following link.
Proof of concept implementation
This repository includes a simple reference implementation (in Python3), and proof-of-concept, of the DPHT proposal. In particular, we currently demonstrate the feasibility of our health tokens and evaluate the error introduced by differential privacy for different values of epsilon. To generate an example health token run GenerateQRToken.py, to verify run VerifyQRToken.py. Credentials, which can be displayed as standard QR codes, are signed using ECDSA over brainpoolP512r1 and comprise a randomised user token. Credentials are completely self-contained and can be verified offline, without interacting with the signer. Revocation is based on distributing revoked CIDs to verifiers. The associated error analysis is generated when GenerateQRToken.py is run. The value of epsilon can, of course, be altered.
- Example credential comprising a random user health token and a valid 512-bit ECDSA signature:
- Example simulation for a range of 1 to 200 users, iterated 50 times:
Running the code
The requirements.txt file contains all dependencies. To run the implementation you can use the following commands.
virtualenv venv
source venv/bin/activate
pip install -r requirements.txt
python3 Generate_QR_Token.py
python3 Verify_QR_Token.py
Owner
- Name: The Alan Turing Institute
- Login: alan-turing-institute
- Kind: organization
- Email: info@turing.ac.uk
- Website: https://turing.ac.uk
- Repositories: 477
- Profile: https://github.com/alan-turing-institute
The UK's national institute for data science and artificial intelligence.
GitHub Events
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- Issues event: 1
Last Year
- Issues event: 1
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Last synced: about 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Chris Hicks | c****s@t****k | 4 |
| David Butler | d****d@q****h | 3 |
| mathsjames | j****1@h****m | 1 |
Committer Domains (Top 20 + Academic)
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- mhauru (1)
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Dependencies
- image *
- matplotlib *
- numpy *
- opencv-python *
- pyOpenSSL *
- pyzbar *
- qrcode *
- zbar-py *
- zbarlight *