{"title":"Modelling Botnet Propagation in Networks with Layered Defences","authors":"Dilara Acarali, M. Rajarajan, N. Komninos","doi":"10.1109/ISNCC.2018.8530934","DOIUrl":null,"url":null,"abstract":"Botnets are still a pertinent threat to our digital infrastructure and a central topic for study in the cyber-research community. At the start of a botnet's life, the aim of the botmaster is to achieve enough spread to make their botnet functional and as potent as possible. Therefore, propagation dynamics are a vital area to address in order to effectively defend against this type of malware. Over the years, there have been many propagation models based on the principles of disease spread but these often do not take specific network characteristics into account. In this paper, we propose the novel use of a probabilistic adaptation of the SEIR (Susceptible, Exposed, Infected, Recovered) model applied to defence-in-depth networks with heterogeneous contact rates and node impact. We test this approach through numerical simulation and discuss our findings.","PeriodicalId":313846,"journal":{"name":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Symposium on Networks, Computers and Communications (ISNCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISNCC.2018.8530934","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Botnets are still a pertinent threat to our digital infrastructure and a central topic for study in the cyber-research community. At the start of a botnet's life, the aim of the botmaster is to achieve enough spread to make their botnet functional and as potent as possible. Therefore, propagation dynamics are a vital area to address in order to effectively defend against this type of malware. Over the years, there have been many propagation models based on the principles of disease spread but these often do not take specific network characteristics into account. In this paper, we propose the novel use of a probabilistic adaptation of the SEIR (Susceptible, Exposed, Infected, Recovered) model applied to defence-in-depth networks with heterogeneous contact rates and node impact. We test this approach through numerical simulation and discuss our findings.