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lazer ===== A library for lattice-based zero-knowledge proofs. Dependencies ------------ The following hardware and software is required to build and run lazer: - Linux amd64 / x86-64 system - kernel version >= 4.18 - avx512 and aes instruction set extensions - gcc compiler >= 13.2 - make >= 4.2, cmake >= 3.26 - sagemath >= 10.2 - python3 >= 3.10, its development package and the cffi package The following software is required to build the documentation: - sphinx >= 5.3 and the sphinxcontrib-bibtex package The package was tested on Ubuntu 20.04 LTS and RHEL 8.10 with an 11th Gen Intel Core i7-11850H @ 2.50GHz and with the dependencies' versions equal to the listed above. We assume that it works with greater versions as well, as long as they are backward compatible. It *may* work with lesser versions as well. Note that during compilation, the cpu_features package will be cloned from GitHub, so also git and an internet connection are required. Building the library -------------------- To build the lazer C library, from the base directory, run: `make all` Optional: use make's `-j` option to speed up compilation. To build lazer's python module, change to the `python` subdirectory and run: `make` (If this step fails, check that the python development package is installed.) Building and viewing the documentation -------------------------------------- To build the html documentation, change to the `docs` subdirectory and run: `make html` (If you have multiple python versions installed, make sure sphinx uses the same version that was used to build the python module.) To view the documentation open `build/html/index.html` in a browser e.g.: `firefox build/html/index.html` Building the C demos -------------------- The `demos` subdirectory has the C demos: - a blind signature implementation in `blindsig` - a PoK of Kyber1024 secrets (paper section 3.2,3.3) in `kyber1024` To build a demo, go to the corresponding subdirectory and run: `make` This creates an executable called `<name>-demo`. Run the demo via: `./<name>-demo` Building and running the python demos for linear relations with norms --------------------------------------------------------------------- In the `python` subdirectory are all the python demos mentioned in the paper: - an anonymous credentials (paper section 6.2) in `anon_cred` - a blind signature implementation in `blindsig` - a PoK of Kyber1024 secrets (paper section 6.1) in `kyber1024` - the proof required in the Swoosh NIKE in `swoosh` - a proof for the general lattice relation As=t in `demo` To build a demo, go to the corresponding subdirectory and run: `make` Each demo is implemented in a python script with the same name as its directory i.e., `<demo>.py`. To run a demo, go to the corresponding subdirectory `<demo>` and run: `python3 <demo>.py` Running the python demo for LaBRADOR ------------------------------------ An aggregate signature (paper section 6.3) implementation is in the `python` subdirectory. Run it via: `python3 agg_sig.py` Generating the demos' proof parameters from a specification ----------------------------------------------------------- A demo's proof parameters are specified in files named `*params.py` in the demo's subdirectory. For convenience, the code gererated from those specifications is included in the package (the `*params.h` header files) such that make only runs the code generator when the specification is changed (or when the header file was deleted). Since the code generator is a sagemath script (`scripts/lin-codegen.sage`) that calls the lattice-estimator multiple times, the code generation process may take multiple minutes, especially for large parameter set, like for Swoosh. The code generator can be used from the `scripts` subdirectory via: `sage lin-codegen.sage <specification> > <headerfile>` Instructions for artifact evaluation and result reproduction ------------------------------------------------------------ 1. Set up a system that meets lazer's requirements decribed above. 2. Obtain and build the library and demos as described above. 3. The code for kyber proof in C from sections 3.2, 3.3 was extended by a main function and sample inpts and is available as a runnable demo in `demos/kyber1024/kyber1024-demo`. 4. The code for kyber proof in python from section 6.1 is available as a runnable demo in `python/kyber1024/kyber1024.py`. 5. The code for the anonymous credentials from section 6.2 is avalable as a runnable demo in `python/anon_cred/anon_cred.py`. 6. The code for the aggregate signature from section 6.3 is available as a runnable demo in `python/agg_sig.py`. 7. Detailed descriptions of the demos are in the documentation. 8. If you want to do anything beyond verifying the paper's results, check out the documentation of the python module's interface.
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