Roland Gabriel, Tobias Hoppe, Alexander Pastwa, Sebastian Sowa
{"title":"Analyzing Malware Log Data to Support Security Information and Event Management: Some Research Results","authors":"Roland Gabriel, Tobias Hoppe, Alexander Pastwa, Sebastian Sowa","doi":"10.1109/DBKDA.2009.26","DOIUrl":null,"url":null,"abstract":"Enterprise information infrastructures are generally characterized by a multitude of information systems which support decision makers in fulfilling their duties. The object of information security management is the protection of these systems, whereas security information and event management (SIEM) addresses those information management tasks which focus on the short term handling of events, as well as on the long term improvement of the entire information security architectures. This is carried out based on those data which can be logged and collected within the enterprise information security infrastructure. An especially interesting type of log data is data created by anti-malware software. This paper demonstrates in the context of a project case study that data mining (DM) is a well suited approach to detect hidden patterns in malware data and thus to support SIEM.","PeriodicalId":231150,"journal":{"name":"2009 First International Confernce on Advances in Databases, Knowledge, and Data Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 First International Confernce on Advances in Databases, Knowledge, and Data Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DBKDA.2009.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27
Abstract
Enterprise information infrastructures are generally characterized by a multitude of information systems which support decision makers in fulfilling their duties. The object of information security management is the protection of these systems, whereas security information and event management (SIEM) addresses those information management tasks which focus on the short term handling of events, as well as on the long term improvement of the entire information security architectures. This is carried out based on those data which can be logged and collected within the enterprise information security infrastructure. An especially interesting type of log data is data created by anti-malware software. This paper demonstrates in the context of a project case study that data mining (DM) is a well suited approach to detect hidden patterns in malware data and thus to support SIEM.