{"title":"Knowledge Graph Based Adversarial Radar Threat Assessment","authors":"Chenyu Zhu, Yue Li, Xinyue Hou, Peng Wang, Xiaoyan Peng","doi":"10.1109/icicse55337.2022.9828881","DOIUrl":null,"url":null,"abstract":"In the field of military equipment knowledge, there are a large number of equipment models, weapon types, working parameters, and other time-frequency-space data information, among which there is a lot of valuable information. At present, when combat-related personnel face this massive knowledge, they cannot efficiently obtain the key knowledge, which means that they cannot provide effective guidance based on the potential key knowledge. To solve this problem, based on the investigation and analysis of the existing knowledge graph construction method, we excavate and extract military equipment knowledge, instantiate and correlate different weapon equipment, and construct the knowledge graph of military equipment. Its construction can not only deeply study the key technical difficulties of the graph in this field, but also has strong strategic support for the future development of this field. In the end, we propose a threat assessment for target radar with a TransE inference model based on the knowledge graph.","PeriodicalId":177985,"journal":{"name":"2022 IEEE 2nd International Conference on Information Communication and Software Engineering (ICICSE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 2nd International Conference on Information Communication and Software Engineering (ICICSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icicse55337.2022.9828881","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the field of military equipment knowledge, there are a large number of equipment models, weapon types, working parameters, and other time-frequency-space data information, among which there is a lot of valuable information. At present, when combat-related personnel face this massive knowledge, they cannot efficiently obtain the key knowledge, which means that they cannot provide effective guidance based on the potential key knowledge. To solve this problem, based on the investigation and analysis of the existing knowledge graph construction method, we excavate and extract military equipment knowledge, instantiate and correlate different weapon equipment, and construct the knowledge graph of military equipment. Its construction can not only deeply study the key technical difficulties of the graph in this field, but also has strong strategic support for the future development of this field. In the end, we propose a threat assessment for target radar with a TransE inference model based on the knowledge graph.