{"title":"Sebek系统监测的动态滤波技术","authors":"E. Balas, G. Travis, C. Viecco","doi":"10.1109/IAW.2006.1652106","DOIUrl":null,"url":null,"abstract":"In this paper we investigate the performance limits of system call based monitoring tools using the Linux version of Sebek as a focal point. We quantify the amount of uninteresting data that it collects and illustrate the problems that this creates: detection of Sebek, amount of work to analyze data, and data privacy. To mitigate these problems we propose a dynamic filtering technique. Finally we evaluate the performance of an implementation of this technique","PeriodicalId":326306,"journal":{"name":"2006 IEEE Information Assurance Workshop","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Dynamic Filtering Technique for Sebek System Monitoring\",\"authors\":\"E. Balas, G. Travis, C. Viecco\",\"doi\":\"10.1109/IAW.2006.1652106\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we investigate the performance limits of system call based monitoring tools using the Linux version of Sebek as a focal point. We quantify the amount of uninteresting data that it collects and illustrate the problems that this creates: detection of Sebek, amount of work to analyze data, and data privacy. To mitigate these problems we propose a dynamic filtering technique. Finally we evaluate the performance of an implementation of this technique\",\"PeriodicalId\":326306,\"journal\":{\"name\":\"2006 IEEE Information Assurance Workshop\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE Information Assurance Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAW.2006.1652106\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Information Assurance Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAW.2006.1652106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Dynamic Filtering Technique for Sebek System Monitoring
In this paper we investigate the performance limits of system call based monitoring tools using the Linux version of Sebek as a focal point. We quantify the amount of uninteresting data that it collects and illustrate the problems that this creates: detection of Sebek, amount of work to analyze data, and data privacy. To mitigate these problems we propose a dynamic filtering technique. Finally we evaluate the performance of an implementation of this technique