Router ownership detection method and system based on IP connection probability classification

Abstract

The invention belongs to the technical field of network topology modeling, and particularly relates to a router ownership detection method and system based on IP connection probability classification,and the method comprises the steps: dividing IP connection into intra-domain connection and inter-domain connection, taking an IP connection type as a probability model hidden variable, and taking the probability that connection features appear in different connection types as a probability model parameter; marking each IP connection initial type in the router-level topology by utilizing router-to-AS mapping in the data set; estimating probability model parameters by utilizing expectation maximization, and taking the connection type with higher probability as the connection type of the feature corresponding to the connection feature vector by utilizing naive Bayesian classification in each iteration until a model convergence condition is reached; and determining the AS to which the routerlocated in the same AS as the trace detection target IP belongs through a voting mechanism. According to the method, the characteristics of the data can be better applied instead of only depending onsubjective experience judgment, the accuracy and effectiveness of router ownership detection can be improved, and the method has a higher application value.

Description

technical field [0001] The invention belongs to the technical field of network topology modeling, in particular to a router ownership detection method and system based on IP connection probability classification. Background technique [0002] An autonomous system (Autonomous System, AS) is a group of routers operated and managed by one or more network operators, with a single and clearly defined routing policy. Router ownership inference is an important challenge in Internet topology research, which can combine router-level and AS-level Internet topologies. Router ownership inference relies on IP-level network topology measurements (such as traceroute), router interface alias resolution techniques, and IP-to-AS mapping techniques, aiming at assigning routers to their ASs. Inferring router ownership is beneficial for accurate modeling of AS-level topology, analysis of network resilience and robustness, detection of inter-domain congestion, etc. In the router-level topology ...

AI Technical Summary

Problems solved by technology

Considering security and competition factors, operators tend to hide their own network topology, making it difficult to obtain real verification data to verify the results

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