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mpc_graph_theory_lib (an SCALE-MAMBA implementation for Basic Graph Theory)

forthebadge
This repository includes (currently we only recommend experimentation):

  • Basic random sampling using Dijkstra with cubic complexity from Aly et al.
  • Improved Dijkstra with quadratic complexity from Aly and Cleemput.
  • Will include complete test files.

Pre-requisites

  • numpy 1.16 or above. (exclusively to test, which in this context means, execute test_graph.mpc).

Installation and Configuration

  1. Download and configure tii-mpclib.

  2. That's it the Dijkstra algorithm over arithmetic circuits (without depending on ORAM) are included in the mpc_graph_lib.py:

  3. You can now run them and check all tests are in green. (NOT in red.)

Roadmap

We understand several Items are missing from this library. We have plans to populate the following:

  • Complete set of tests for dijkstra_optimized and sorting functionality on test_graph.mpc.
  • Complete the permutation functionality missing in the library.

License

Contact Information:

If you have questions please contact any of the authors. Current repo maintainer is: Abdelrahaman ALY.

Authors:

Abdelrahaman ALY