{"title":"Privacy Illusion: Beware of Unpadded DoH","authors":"Karel Hynek, T. Čejka","doi":"10.1109/IEMCON51383.2020.9284864","DOIUrl":null,"url":null,"abstract":"DNS over HTTPS (DoH) has been created with ambitions to improve the privacy of users on the internet. Domain names that are being resolved by DoH are transferred via an encrypted channel, ensures nobody should be able to read the content. However, even though the communication is encrypted, we show that it still leaks some private information, which can be misused. Therefore, this paper studies the behavior of the DoH protocol implementation in Firefox and Chrome web-browsers, and the level of detail that can be revealed by observing and analyzing packet-level information. The aim of this paper is to evaluate and highlight discovered privacy weaknesses hidden in DoH. By the trained machine learning classifier, it is possible to infer individual domain names only from the captured encrypted DoH connection. The resulting trained classifier can infer domain name from encrypted DNS traffic with surprisingly high accuracy up to 90% on HTTP 1.1, and up to 70% on HTTP 2 protocol.","PeriodicalId":6871,"journal":{"name":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"6 1","pages":"0621-0628"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMCON51383.2020.9284864","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
DNS over HTTPS (DoH) has been created with ambitions to improve the privacy of users on the internet. Domain names that are being resolved by DoH are transferred via an encrypted channel, ensures nobody should be able to read the content. However, even though the communication is encrypted, we show that it still leaks some private information, which can be misused. Therefore, this paper studies the behavior of the DoH protocol implementation in Firefox and Chrome web-browsers, and the level of detail that can be revealed by observing and analyzing packet-level information. The aim of this paper is to evaluate and highlight discovered privacy weaknesses hidden in DoH. By the trained machine learning classifier, it is possible to infer individual domain names only from the captured encrypted DoH connection. The resulting trained classifier can infer domain name from encrypted DNS traffic with surprisingly high accuracy up to 90% on HTTP 1.1, and up to 70% on HTTP 2 protocol.