System for enhanced anomaly recognition in network topologies using interactive visualization

A computer program product for anomaly recognition in network topologies using interactive visualization, the computer program product comprising a non-transitory computer-readable medium comprising code causing an apparatus to:

• determine that an end-point device is associated with anomalous activity;
• capture, using a virtual reality application installed on a user input device, real-time network traffic associated with the end-point device;
• generate a multi-dimensional model of the real-time network traffic associated with the end-point device, wherein the multi-dimensional model comprises a stack of data layers for visualization of the real-time network traffic, wherein the stack of data layers comprises a network topology layer, a network traffic layer, a performance metric layer, an incident layer, an application data layer, and nodal information layer;
• display, via the virtual reality application, the multi-dimensional model to a user;
• isolate, using the virtual reality application, network traffic associated with the anomalous activity;
• initiate spatial and temporal traffic analysis on the anomalous activity;
• determine, using the virtual reality application, an initiator and a recipient associated with the anomalous activity based on the spatial and temporal traffic analysis;
• determine a remedial action based on the spatial and temporal traffic analysis to mitigate effects of the anomalous activity based on the initiator and the recipient associated with the anomalous activity;
• and
• implement the remedial action on the end-point device.

A method for anomaly recognition in network topologies using interactive visualization, the method comprising:

• determining that an end-point device is associated with anomalous activity;
• capturing, using a virtual reality application installed on a user input device, real-time network traffic associated with the end-point device;
• generating a multi-dimensional model of the real-time network traffic associated with the end-point device, wherein the multi-dimensional model comprises a stack of data layers for visualization of the real-time network traffic, wherein the stack of data layers comprises a network topology layer, a network traffic layer, a performance metric layer, an incident layer, an application data layer, and nodal information layer;
• displaying, via the virtual reality application, the multi-dimensional model to a user;
• isolating, using the virtual reality application, network traffic associated with the anomalous activity;
• initiating spatial and temporal traffic analysis on the anomalous activity;
• determining, using the virtual reality application, an initiator and a recipient associated with the anomalous activity based on the spatial and temporal traffic analysis;
• determining a remedial action based on the spatial and temporal traffic analysis to mitigate effects of the anomalous activity based on the initiator and the recipient associated with the anomalous activity;
• and
• implementing the remedial action on the end-point device.