{"title":"考虑良性蠕虫和链路预测方法的复杂网络中蠕虫传播模型动力学","authors":"Elham Asadi, Soodeh Hosseini","doi":"10.1002/eng2.13110","DOIUrl":null,"url":null,"abstract":"<p>In this paper, the spread of worms as a type of malware is modeled with epidemic models. In the proposed model, we have considered the defense mechanism of the benign worm, link prediction, and quarantine of the infected nodes as methods to reduce the spread of the worm in complex networks. For the benign worm, the parameters of the ability to detect vulnerable nodes and the ability to immunization nodes have been considered, and we have investigated their role in reducing the spread of the worm in the network. The vulnerability list of the benign worm is considered as another characteristic of the benign worm and its role in the spread of the worm is analyzed. In the context of dynamic analysis of the model, we have obtained the initial equilibrium point and the basic reproduction ratio. Finally, the proposed model is evaluated on the Barabasi Albert artificial network and the standard data sets and compared with the SIR and SIRV models.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"7 2","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.13110","citationCount":"0","resultStr":"{\"title\":\"Dynamics of Worm Propagation Model in Complex Networks Considering Benign Worm and Link Prediction Approach\",\"authors\":\"Elham Asadi, Soodeh Hosseini\",\"doi\":\"10.1002/eng2.13110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In this paper, the spread of worms as a type of malware is modeled with epidemic models. In the proposed model, we have considered the defense mechanism of the benign worm, link prediction, and quarantine of the infected nodes as methods to reduce the spread of the worm in complex networks. For the benign worm, the parameters of the ability to detect vulnerable nodes and the ability to immunization nodes have been considered, and we have investigated their role in reducing the spread of the worm in the network. The vulnerability list of the benign worm is considered as another characteristic of the benign worm and its role in the spread of the worm is analyzed. In the context of dynamic analysis of the model, we have obtained the initial equilibrium point and the basic reproduction ratio. Finally, the proposed model is evaluated on the Barabasi Albert artificial network and the standard data sets and compared with the SIR and SIRV models.</p>\",\"PeriodicalId\":72922,\"journal\":{\"name\":\"Engineering reports : open access\",\"volume\":\"7 2\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-02-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.13110\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering reports : open access\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/eng2.13110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering reports : open access","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/eng2.13110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Dynamics of Worm Propagation Model in Complex Networks Considering Benign Worm and Link Prediction Approach
In this paper, the spread of worms as a type of malware is modeled with epidemic models. In the proposed model, we have considered the defense mechanism of the benign worm, link prediction, and quarantine of the infected nodes as methods to reduce the spread of the worm in complex networks. For the benign worm, the parameters of the ability to detect vulnerable nodes and the ability to immunization nodes have been considered, and we have investigated their role in reducing the spread of the worm in the network. The vulnerability list of the benign worm is considered as another characteristic of the benign worm and its role in the spread of the worm is analyzed. In the context of dynamic analysis of the model, we have obtained the initial equilibrium point and the basic reproduction ratio. Finally, the proposed model is evaluated on the Barabasi Albert artificial network and the standard data sets and compared with the SIR and SIRV models.