System for intelligent automated simulation of penetration testing and isolation of vulnerable distributed electronic data registers

A computer program product for intelligent automated simulation of penetration testing and isolation of vulnerable distributed electronic data registers, the computer program product comprising a non-transitory computer-readable medium comprising code causing an apparatus to perform the steps of:

• continuously monitoring a distributed register network to extract metadata associated with the distributed register network;
• based on the extracted metadata, constructing a knowledge graph comprising information regarding the distributed register network;
• detecting a change in the distributed register network based on the knowledge graph;
• using a machine learning algorithm, identifying a potential vulnerability in a portion of the distributed register network based on the change in the distributed register network, wherein identifying the potential vulnerability comprises:
• computing a vulnerability score for each node, block, and network of the distributed register network;
• and
• generating a visual heatmap of the vulnerability scores comprising a scatter plot with each node, block, and network of the distributed register network represented by points within the scatter plot, wherein a size and a color of the points correspond to the vulnerability scores;
• generating a testing environment comprising a simulation of the portion of the distributed register network;
• executing penetration testing of the simulation based on the potential vulnerability;
• and
• based on results of the penetration testing, updating security rules associated with the distributed register network.

A computer-implemented method for intelligent automated simulation of penetration testing and isolation of vulnerable distributed electronic data registers, the computer-implemented method comprising:

• continuously monitoring a distributed register network to extract metadata associated with the distributed register network;
• based on the extracted metadata, constructing a knowledge graph comprising information regarding the distributed register network;
• detecting a change in the distributed register network based on the knowledge graph;
• using a machine learning algorithm, identifying a potential vulnerability in a portion of the distributed register network based on the change in the distributed register network, wherein identifying the potential vulnerability comprises:
• computing a vulnerability score for each node, block, and network of the distributed register network;
• and
• generating a visual heatmap of the vulnerability scores comprising a scatter plot with each node, block, and network of the distributed register network represented by points within the scatter plot, wherein a size and a color of the points correspond to the vulnerability scores;
• generating a testing environment comprising a simulation of the portion of the distributed register network;
• executing penetration testing of the simulation based on the potential vulnerability;
• and
• based on results of the penetration testing, updating security rules associated with the distributed register network.