AS Knowledge Graph Implementation And Visualization

The Internet consists of tens of thousands of AS(Autonomous System)distributed worldwide.Each AS belongs to a specific organization,such as technology companies,universities,government agencies,and scientific research institutions.It is an independent internet composed of routing transmission equipment and routing protocols.It has the same routing strategy and is managed and operated by the same technical management department.The autonomous domain system is the infrastructure of cyberspace and the basic unit for organizing the basic resources of the Internet.Autonomous domain resources have multi-dimensional attributes,including static attributes such as institutional ownership,national ownership,industry ownership,geographic territory,network size,and network level,as well as dynamic attributes such as routing prefix announcement stability,path change stability,and connection relationships.The multi-dimensional attributes of autonomous domains reflect the changes in routing behavior and clustering relationships between networks to some extent.At present,the multi-dimensional attributes of the autonomous domain have various forms,and the correlation between data is low,so it is difficult to form high-value knowledge data.In order to solve these problems,this paper proposes a technology for mapping the knowledge pedigree of autonomous domain resources in the Internet.Extract,condense,and correlate multi-dimensional attribute information of autonomous domains from Internet information resources,draw knowledge maps of autonomous domain resources,and discover key strategic fortresses,hierarchical clustering relationships,and address inclusion relationships between networks,to locate and secure routing attack defense and routing events Evaluation provides data support.The work of this paper is mainly divided into three parts.First of all,the data collection and merging of AS multi-dimensional attributes are realized,and the multi-dimensional attributes of AS are obtained from different channels on the Internet,including the autonomous domain text registration information,the long-term stable relationship of AS implicit in historical routing messages,and third parties and autonomous domains.Relevant organizations and other information;Secondly,based on the knowledge graph analysis technology,through machine learning and text semantic analysis,extract the extension attributes associated with the autonomous domain ontology,including industry belonging,geographical territory,network scale,network level and other information,and Associate with the cyberspace IP ontology,domain name ontology,and website resources to form a networked knowledge structure.Finally,based on the formed knowledge map of the autonomous domain,the intelligent search of the autonomous domain resources is realized,the autonomous domain resources are mapped to the three-dimensional geographic space,and the distribution of the autonomous domain resources in the geographic space is displayed intuitively.The research results of this paper are of great significance for the detection of routing attack events and the perception of routing security status.