DDoS attack traffic peak value prediction method based on machine learning
A technology of attacking traffic and machine learning, applied in digital transmission systems, data exchange networks, electrical components, etc., can solve problems such as routing strategy failure, protection effect reduction, failure, etc.
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment
[0046] Such as figure 1 The system shown is mainly divided into two parts, the first part is model training and the second part is traffic prediction. In the model training part, this system uses the existing DDoS data set for feature extraction and uses the method of integrated learning for training. In the traffic prediction part, when a DDoS attack is detected, the corresponding attack traffic input feature extraction module extracts the attack time feature set, and the normal traffic feature set and the attack feature set are spliced together and input into the trained model. The model outputs predictions based on the set of features.
[0047] During the training phase, according to figure 2 , firstly find the existing public DDoS attack traffic data set, which is MIT DARPA1998DataSet used in this embodiment. Extract 90% of the data as the training data, and for each attack i in the training data, extract the traffic of T(i) seconds from the beginning of the attack t...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More 


