Synthetic Network Simulation Engine for Secure Financial Data Testing
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Solution Overview
Problem
Complexity and confidentiality of data in commercial-scale computer networks, particularly in the financial industry, hinder effective simulation and testing of network behavior and performance due to security and privacy concerns, as well as data ownership issues.
Innovation Solution
A network simulation system comprising a request processor and a simulation engine that generates realistic event data based on network topology input, including node and relationship parameters, allowing for stochastic event generation and modification of network conditions, thus simulating increased or decreased traffic to assess network performance without compromising data privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network simulation uses real confidential data from financial networks, then the simulation realism and accuracy are improved, but data security and privacy requirements are violated
Solution Approach 1:
The patent creates synthetic copies of network data that replicate the statistical properties, relationships, and behavioral patterns of real financial network data without containing actual sensitive information. The simulation engine generates artificial transaction records, node relationships, and network topologies that mirror real network characteristics while being completely synthetic, thus achieving high simulation fidelity without compromising data security.
2Measurement precision
If network simulation includes detailed node and relationship data, then the simulation realism is improved, but data ownership issues and access restrictions are violated
Solution Approach 1:
The system enables organizations to generate their own synthetic network simulation data using the simulation engine, eliminating the need to access or share actual confidential network data. The engine uses publicly available or lightly sanitized input parameters to autonomously generate realistic simulation datasets, allowing each organization to serve its own data needs without violating ownership or access restrictions of other participants' data.
3Productivity
If network simulation processes large volumes of transaction data, then the network performance analysis capability is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent applies different levels of detail and processing intensity to different portions of the simulation data based on their importance to performance analysis. Critical network nodes and relationships receive more detailed modeling and processing, while less significant elements use simplified representations. This selective approach maintains high analysis capability for key performance indicators while reducing overall computational complexity.
Data Source
AI summary
A system for simulating a network includes a request processor operably connected to a simulation engine. The request processor receives a request for network simulation data and input data relating to a topology of a network including node data and relationship data with relationship parameters. The simulation engine outputs a stream of event data based on the relationship data to the request processor and generates respective events by determining a source node and a destination node and corresponding relationship parameters, determining an event time, and determining a transfer value. The simulation engine also, in response to a determination that the transfer value does not exceed a current resource level of the source node, decrements the current resource level of the source node by the transfer value, increments a current resource level of the destination node by the transfer value, generates event data, spawns an event generation process, transmits update data, spawns at least one additional event generation process, and streams the event data to the request processor for transmission to a user device.