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US 11,695,792 B2Granted
Leveraging synthetic traffic data samples for flow classifier training
AssigneeCisco Technology, Inc.
InventorsBlake Harrell Anderson, David McGrew
Life of this patent
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Abstract
In one embodiment, a device in a network receives traffic data regarding a plurality of observed traffic flows. The device maps one or more characteristics of the observed traffic flows from the traffic data to traffic characteristics associated with a targeted deployment environment. The device generates synthetic traffic data based on the mapped traffic characteristics associated with the targeted deployment environment. The device trains a machine learning-based traffic classifier using the synthetic traffic data.
Claims20
A method comprising:
- receiving, at a device in a network, traffic data regarding a plurality of observed traffic flows;
- determining, by the device, one or more environment parameters associated with a targeted deployment environment in which a machine learning-based traffic classifier is to be deployed, wherein the targeted deployment environment is different than the network in which the traffic data was received;
- modifying, by the device, one or more samples of the plurality of observed traffic flows from the traffic data to match traffic characteristics of the targeted deployment environment based on the one or more environment parameters associated with the targeted deployment environment;
- creating, by the device, synthetic traffic data that resembles actual traffic data expected in the targeted deployment environment based on the one or more modified samples, wherein the synthetic traffic data is not actually observed in the network;
- and
- training, by the device, the machine learning-based traffic classifier using the synthetic traffic data for deployment in the targeted deployment environment.
3 more elements
An apparatus, comprising:
- one or more network interfaces to communicate with a network;
- a processor coupled to the one or more network interfaces and configured to execute one or more processes;
- and
- a memory configured to store a process executable by the processor, the process when executed operable to:
- receive traffic data regarding a plurality of observed traffic flows in the network;
- determine one or more environment parameters associated with a targeted deployment environment in which a machine learning-based traffic classifier is to be deployed, wherein the targeted deployment environment is different than the network in which the traffic data was received;
- modify one or more samples of the plurality of observed traffic flows from the traffic data to match traffic characteristics of the targeted deployment environment based on the one or more environment parameters associated with the targeted deployment environment;
- create synthetic traffic data that resembles actual traffic data expected in the targeted deployment environment based on the one or more modified samples, wherein the synthetic traffic data is not actually observed in the network;
- and
- train the machine learning-based traffic classifier using the synthetic traffic data for deployment in the targeted deployment environment.
7 more elements
A tangible, non-transitory, computer-readable medium storing program instructions that cause a device in a network to execute a process comprising:
- receiving, at the device, traffic data regarding a plurality of observed traffic flows;
- determining, by the device, one or more environment parameters associated with a targeted deployment environment in which a machine learning-based traffic classifier is to be deployed, wherein the targeted deployment environment is different than the network in which the traffic data was received;
- modifying, by the device, one or more samples of the plurality of observed traffic flows from the traffic data to match traffic characteristics of the targeted deployment environment based on the one or more environment parameters associated with the targeted deployment environment;
- creating, by the device, synthetic traffic data that resembles actual traffic data expected in the targeted deployment environment based on the one or more modified samples, wherein the synthetic traffic data is not actually observed in the network;
- and
- training, by the device, the machine learning-based traffic classifier using the synthetic traffic data for deployment in the targeted deployment environment.
3 more elements
Dependencies are inferred from the claim text.