Network Security Model Accuracy Estimation via Simulated Traffic
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Solution Overview
Problem
Existing network security policies lack a method to accurately estimate their accuracy before being applied to actual network traffic, leading to uncertainty and risk during enforcement.
Innovation Solution
A computer system automatically tests a network communication model by predicting whether simulated traffic should be allowed on the network and estimating the model's accuracy based on these predictions, even before applying the model to actual traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a network communication model is applied to actual network traffic, then the model can be enforced to secure the network, but the accuracy and reliability of the model remain unknown, creating security risk
Solution Approach 1:
The patent generates simulated network traffic data and tests the network communication model against this simulated data before deploying it to actual network traffic. This preliminary testing allows the accuracy of the model to be estimated in advance, ensuring that only models meeting accuracy thresholds are deployed, thereby reducing security risks while maintaining reliability
Solution Approach 2:
The patent introduces simulated network traffic as an intermediary between model development and actual network traffic enforcement. This simulated traffic serves as a safe testing medium that allows accuracy validation without exposing the actual network to potential risks from inaccurate models, bridging the gap between model creation and deployment
2Measurement precision
If the accuracy of a network communication model is tested on actual network traffic, then accurate measurements can be obtained, but the model cannot be deployed until testing is complete, causing time loss
Solution Approach 1:
The patent creates copies of actual network traffic characteristics in the form of simulated traffic data that preserves the statistical properties and patterns of real traffic. This copying allows accuracy testing to be performed on the simulated data in parallel with model development, enabling rapid validation without waiting for actual traffic analysis, thus reducing deployment time while maintaining measurement precision
Solution Approach 2:
By performing accuracy testing on simulated traffic data before actual deployment, the system eliminates the need to wait for post-deployment validation. The preliminary testing on copies of real traffic characteristics allows the model to be ready for immediate deployment once accuracy thresholds are met, eliminating time loss
Data Source
AI summary
A computer system automatically tests a network communication model by predicting whether particular traffic (whether actual or simulated) should be allowed on the network, and then estimating the accuracy of the network communication model based on the prediction. Such an estimate may be generated even before the model has been applied to traffic on the network. For example, steps can include observing positive data associated with a network; generating a network communication model based on the positive data; generating negative data based on the network communication model; calculating a precision of the network communication model based on the network communication model and the negative data; and calculating an accuracy of the network communication model based on one or more of the precision of the network communication model, or the network communication model and the positive data.