{"title":"基于上下文的高级持续威胁检测框架","authors":"P. Giura, Wei Wang","doi":"10.1109/CyberSecurity.2012.16","DOIUrl":null,"url":null,"abstract":"Besides a large set of malware categories such as worms and Trojan horses, Advanced Persistent Threat (APT) is another more sophisticated attack entity emerging in the cyber threats environment. In this paper we propose a model of the APT detection problem as well as a methodology to implement it on a generic organization network. From our knowledge, the proposed method is the first to address the problem of modeling an APT and to provide a possible detection framework.","PeriodicalId":162858,"journal":{"name":"2012 International Conference on Cyber Security","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"86","resultStr":"{\"title\":\"A Context-Based Detection Framework for Advanced Persistent Threats\",\"authors\":\"P. Giura, Wei Wang\",\"doi\":\"10.1109/CyberSecurity.2012.16\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Besides a large set of malware categories such as worms and Trojan horses, Advanced Persistent Threat (APT) is another more sophisticated attack entity emerging in the cyber threats environment. In this paper we propose a model of the APT detection problem as well as a methodology to implement it on a generic organization network. From our knowledge, the proposed method is the first to address the problem of modeling an APT and to provide a possible detection framework.\",\"PeriodicalId\":162858,\"journal\":{\"name\":\"2012 International Conference on Cyber Security\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"86\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Cyber Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CyberSecurity.2012.16\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Cyber Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CyberSecurity.2012.16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Context-Based Detection Framework for Advanced Persistent Threats
Besides a large set of malware categories such as worms and Trojan horses, Advanced Persistent Threat (APT) is another more sophisticated attack entity emerging in the cyber threats environment. In this paper we propose a model of the APT detection problem as well as a methodology to implement it on a generic organization network. From our knowledge, the proposed method is the first to address the problem of modeling an APT and to provide a possible detection framework.