Biblio
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Does Certificate Transparency Break the Web? Measuring Adoption and Error Rate 2019 IEEE Symposium on Security and Privacy (SP). :211—226.
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2019. Certificate Transparency (CT) is an emerging system for enabling the rapid discovery of malicious or misissued certificates. Initially standardized in 2013, CT is now finally beginning to see widespread support. Although CT provides desirable security benefits, web browsers cannot begin requiring all websites to support CT at once, due to the risk of breaking large numbers of websites. We discuss challenges for deployment, analyze the adoption of CT on the web, and measure the error rates experienced by users of the Google Chrome web browser. We find that CT has so far been widely adopted with minimal breakage and warnings. Security researchers often struggle with the tradeoff between security and user frustration: rolling out new security requirements often causes breakage. We view CT as a case study for deploying ecosystem-wide change while trying to minimize end user impact. We discuss the design properties of CT that made its success possible, as well as draw lessons from its risks and pitfalls that could be avoided in future large-scale security deployments.
An Experience Sampling Study of User Reactions to Browser Warnings in the Field. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. :512:1–512:13.
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2018. Web browser warnings should help protect people from malware, phishing, and network attacks. Adhering to warnings keeps people safer online. Recent improvements in warning design have raised adherence rates, but they could still be higher. And prior work suggests many people still do not understand them. Thus, two challenges remain: increasing both comprehension and adherence rates. To dig deeper into user decision making and comprehension of warnings, we performed an experience sampling study of web browser security warnings, which involved surveying over 6,000 Chrome and Firefox users in situ to gather reasons for adhering or not to real warnings. We find these reasons are many and vary with context. Contrary to older prior work, we do not find a single dominant failure in modern warning design—like habituation—that prevents effective decisions. We conclude that further improvements to warnings will require solving a range of smaller contextual misunderstandings.