{"title":"Auto-FBI: a user-friendly approach for secure access to sensitive content on the web","authors":"Mohsen Zohrevandi, R. Bazzi","doi":"10.1145/2523649.2523683","DOIUrl":null,"url":null,"abstract":"We propose a novel and simple approach for securing access to sensitive content on the web. The approach automates the best manual compartmentalization practices for accessing different kinds of content with different browser instances. The automation is transparent to the user and does not require any modification of how non-sensitive content is accessed. For sensitive content, a Fresh Browser Instance (FBI) is automatically created to access the content. Our prototype system Auto-FBI can provide support for novice users with predefined sensitive content sites as well as for more experienced users who can define conflict of interest (COI) classes which allows content from sites in the same user-defined class to coexist in a browser instance. Our initial performance evaluation of Auto-FBI shows that the overhead introduced by the approach is acceptable (less than 160 ms for sites that already have fast load time, but for slow sites the overhead can be as high as 750 ms).","PeriodicalId":127404,"journal":{"name":"Proceedings of the 29th Annual Computer Security Applications Conference","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 29th Annual Computer Security Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2523649.2523683","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
We propose a novel and simple approach for securing access to sensitive content on the web. The approach automates the best manual compartmentalization practices for accessing different kinds of content with different browser instances. The automation is transparent to the user and does not require any modification of how non-sensitive content is accessed. For sensitive content, a Fresh Browser Instance (FBI) is automatically created to access the content. Our prototype system Auto-FBI can provide support for novice users with predefined sensitive content sites as well as for more experienced users who can define conflict of interest (COI) classes which allows content from sites in the same user-defined class to coexist in a browser instance. Our initial performance evaluation of Auto-FBI shows that the overhead introduced by the approach is acceptable (less than 160 ms for sites that already have fast load time, but for slow sites the overhead can be as high as 750 ms).