ReCon is a Universal Reputation Module for Distributed Consensus Protocols. This is the simulation of the protocol written in Python 2.7 based on our paper. Here is a link to a short simulation as well, where we present how to use the simulator: https://drive.google.com/open?id=0B-AIuoQFeJqxOFJyaW9BZm53VE0

The full paper can be found on the following link: https://doi.org/10.1016/j.pmcj.2019.101109

• SciPy
• matplotlib
• Tkinter

Simply compile the recondemo.py python file, and use the graphical interface. To start a simulation, first specify the number of nodes and the initial maliciousness alpha_0 (a value between 0 and 1), and choose your preferred selection function and external reputation, then click on Start!.

Dynamic changes during a simulation:

• You can flip the honesty of nodes with the Botnet function. If you write a positive number, it will turn that many malicious nodes into bad nodes, and if you write a negative number, it will flip that many honest nodes into bad nodes.
• The Sybil function adds the written number of either honest or malicious nodes to the network, based on the sign of the integer (positive for honest, negative for malicious nodes).
• The Remove function is similar to the Sybil one, but it removes the given number of honest or malicious nodes from the network.
• The Track node function tracks the reputation value of the closest honest node to the giver value on the bottom two graphs with a green marker.

Every function starts working on the click of their respective Go! buttons.

The graphs describe the following:

• The main graph is the success rate of the protocol based on the last 100 rounds.
• The bottom left graph is the current ordered reputation distribution in blue and the original reputation distribution in red.
• The bottom right graph is the nodes grouped into 1/10th of all nodes sized tuples, ordered by reputation.
• The small graph under the options is the overall maliciousness of the network.