{"title":"On quantitative dynamic data flow tracking","authors":"Enrico Lovat, Johan Oudinet, A. Pretschner","doi":"10.1145/2557547.2557551","DOIUrl":null,"url":null,"abstract":"We present a non-probabilistic model for dynamic quantitative data flow tracking. Estimations of the amount of data stored in a particular representation at runtime - a file, a window, a network packet - enable the adoption of fine-grained policies which authorize or prohibit partial leaks of data. We prove the correctness of the estimations, provide an implementation that we evaluate w.r.t. precision and performance, and analyze one instantiation at the OS level.","PeriodicalId":90472,"journal":{"name":"CODASPY : proceedings of the ... ACM conference on data and application security and privacy. ACM Conference on Data and Application Security & Privacy","volume":"24 1","pages":"211-222"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CODASPY : proceedings of the ... ACM conference on data and application security and privacy. ACM Conference on Data and Application Security & Privacy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2557547.2557551","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
We present a non-probabilistic model for dynamic quantitative data flow tracking. Estimations of the amount of data stored in a particular representation at runtime - a file, a window, a network packet - enable the adoption of fine-grained policies which authorize or prohibit partial leaks of data. We prove the correctness of the estimations, provide an implementation that we evaluate w.r.t. precision and performance, and analyze one instantiation at the OS level.