{"title":"Hiding from Whom?","authors":"Ksenia Ermoshina, F. Musiani","doi":"10.7202/1058473AR","DOIUrl":null,"url":null,"abstract":"Following Edward Snowden’s revelations, end-to-end encryption is becoming increasingly widespread in messaging tools—solutions that propose a large variety of ways to conceal, obfuscate, disguise private communications and online activities. Designing privacy-enhancing tools requires the identification of a threat model that serves to agree upon an appropriate threshold of anonymity and confidentiality for a particular context of usage. In this article, we discuss different use-cases, from “nothing-to-hide” low-risk situations to high-risk scenarios in war zones or in authoritarian contexts, to question how users, trainers, and developers co-construct threat models, decide which data to conceal, and how to conceal it. We demonstrate that classic oppositions such as high-risk versus low-risk, privacy versus security, should be redefined within a more relational, processual, and contextual approach.","PeriodicalId":42444,"journal":{"name":"Intermedialites","volume":" ","pages":""},"PeriodicalIF":0.1000,"publicationDate":"2019-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.7202/1058473AR","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intermedialites","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7202/1058473AR","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"HUMANITIES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 3
Abstract
Following Edward Snowden’s revelations, end-to-end encryption is becoming increasingly widespread in messaging tools—solutions that propose a large variety of ways to conceal, obfuscate, disguise private communications and online activities. Designing privacy-enhancing tools requires the identification of a threat model that serves to agree upon an appropriate threshold of anonymity and confidentiality for a particular context of usage. In this article, we discuss different use-cases, from “nothing-to-hide” low-risk situations to high-risk scenarios in war zones or in authoritarian contexts, to question how users, trainers, and developers co-construct threat models, decide which data to conceal, and how to conceal it. We demonstrate that classic oppositions such as high-risk versus low-risk, privacy versus security, should be redefined within a more relational, processual, and contextual approach.