Jianhua Sun, Jizha Qin, Shu Chen, Hao Chen, Dingding Li
{"title":"大规模网络中基于社区的病毒免疫模型","authors":"Jianhua Sun, Jizha Qin, Shu Chen, Hao Chen, Dingding Li","doi":"10.1109/SNPD.2007.501","DOIUrl":null,"url":null,"abstract":"With the development of computers and Internet, more and more people use email. Viruses of email have caused large damages. Traditional intentional immunization based on nodes degree does not take the positions of infected nodes into account, and protects the nodes which have high degree. We introduce the concept of community into the research field of virus and immunization, and propose an immunization model based on communities. According to the different stages of virus infection, this model immunizes infected communities or healthy communities, which slows down the virus spreading rate and keeps virus from spreading to more communities. Degree immunization can not keep the virus in a part of communities, and as a result the infected nodes diffuse in almost all communities. Communities immunization can keep the virus in a certain number of communities. These two models are different in the ratio of infected communities and infected communities vector. In summary, communities immunization is different from the degree immunization completely, and is a novel and effective scheme.","PeriodicalId":197058,"journal":{"name":"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Virus Immunization Model Based on Communities in Large Scale Networks\",\"authors\":\"Jianhua Sun, Jizha Qin, Shu Chen, Hao Chen, Dingding Li\",\"doi\":\"10.1109/SNPD.2007.501\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the development of computers and Internet, more and more people use email. Viruses of email have caused large damages. Traditional intentional immunization based on nodes degree does not take the positions of infected nodes into account, and protects the nodes which have high degree. We introduce the concept of community into the research field of virus and immunization, and propose an immunization model based on communities. According to the different stages of virus infection, this model immunizes infected communities or healthy communities, which slows down the virus spreading rate and keeps virus from spreading to more communities. Degree immunization can not keep the virus in a part of communities, and as a result the infected nodes diffuse in almost all communities. Communities immunization can keep the virus in a certain number of communities. These two models are different in the ratio of infected communities and infected communities vector. In summary, communities immunization is different from the degree immunization completely, and is a novel and effective scheme.\",\"PeriodicalId\":197058,\"journal\":{\"name\":\"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)\",\"volume\":\"253 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SNPD.2007.501\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD.2007.501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Virus Immunization Model Based on Communities in Large Scale Networks
With the development of computers and Internet, more and more people use email. Viruses of email have caused large damages. Traditional intentional immunization based on nodes degree does not take the positions of infected nodes into account, and protects the nodes which have high degree. We introduce the concept of community into the research field of virus and immunization, and propose an immunization model based on communities. According to the different stages of virus infection, this model immunizes infected communities or healthy communities, which slows down the virus spreading rate and keeps virus from spreading to more communities. Degree immunization can not keep the virus in a part of communities, and as a result the infected nodes diffuse in almost all communities. Communities immunization can keep the virus in a certain number of communities. These two models are different in the ratio of infected communities and infected communities vector. In summary, communities immunization is different from the degree immunization completely, and is a novel and effective scheme.