The invention relates to a robust IP positioning method based on adaptive graph clipping and
noise disturbance, which comprises the following steps: confirming nodes based on IP addresses or
router nodes and defining an adjacent matrix to form an original graph structure, then clipping low-importance nodes and redundant edges according to a dynamic threshold value based on node mixed importance scores, generating a simplified sub-graph structure, and carrying out adaptive graph clipping and
noise disturbance on the basis of the simplified sub-graph structure.
Random noise disturbance conforming to
Gaussian distribution is applied to node and edge weights on the simplified sub-graph structure, the
noise intensity is adjusted through an adaptive strategy to achieve robustness training of the model, the simplified sub-graph structure is input into the trained model, and node neighbor features are aggregated through multi-layer graph
convolution operation; mapping the final layer node embedding vector into
latitude and
longitude coordinates, and outputting a
latitude and
longitude prediction result of each target IP node; the method has the
advantage of high-precision and robust geographic positioning of large-scale internet IP addresses.