The privacy guaranteed by secure messaging applications relies on users completing an authentication ceremony to verify they are using the proper encryption keys. We examine the feasibility of social authentication, which partially automates the ceremony using social media accounts. We implemented social authentication in Signal and conducted a within-subject user study with 42 participants to compare this with existing methods. To generalize our results, we conducted a Mechanical Turk survey involving 421 respondents. Our results show that users found social authentication to be convenient and fast. They particularly liked verifying keys asynchronously, and viewing social media profiles naturally coincided with how participants thought of verification. However, some participants reacted negatively to integrating social media with Signal, primarily because they distrust social media services. Overall, automating the authentication ceremony and distributing trust with additional service providers is promising, but this infrastructure needs to be more trusted than social media companies.

Secure email is increasingly being touted as usable by novice users, with a push for adoption based on recent concerns about government surveillance. To determine whether secure email is ready for grassroots adoption, we employ a laboratory user study that recruits pairs of novice users to install and use several of the latest systems to exchange secure messages. We present both quantitative and qualitative results from 28 pairs of novices as they use Private WebMail (Pwm), Tutanota, and Virtru and 10 pairs of novices as they use Mailvelope. Participants report being more at ease with this type of study and better able to cope with mistakes since both participants are “on the same page.” We find that users prefer integrated solutions over depot-based solutions and that tutorials are important in helping first-time users. Finally, our results demonstrate that Pretty Good Privacy using manual key management is still unusable for novice users, with 9 of 10 participant pairs failing to complete the study.

Outlier detection has been shown to be a promising machine learning technique for a diverse array of felds and problem areas. However, traditional, supervised outlier detection is not well suited for problems such as network intrusion detection, where proper labelled data is scarce. This has created a focus on extending these approaches to be unsupervised, removing the need for explicit labels, but at a cost of poorer performance compared to their supervised counterparts. Recent work has explored ways of making up for this, such as creating ensembles of diverse models, or even diverse learning algorithms, to jointly classify data. While using unsupervised, heterogeneous ensembles of learning algorithms has been proposed as a viable next step for research, the implications of how these ensembles are built and used has not been explored.

Secure email is increasingly being touted as usable by novice users, with a push for adoption based on recent concerns about government surveillance. To determine whether secure email is ready for grassroots adoption, we employ a laboratory user study that recruits pairs of novice users to install and use several of the latest systems to exchange secure messages. We present both quantitative and qualitative results from 25 pairs of novice users as they use Pwm, Tutanota, and Virtru. Participants report being more at ease with this type of study and better able to cope with mistakes since both participants are "on the same page". We find that users prefer integrated solutions over depot-based solutions, and that tutorials are important in helping first-time users. Hiding the details of how a secure email system provides security can lead to a lack of trust in the system. Participants expressed a desire to use secure email, but few wanted to use it regularly and most were unsure of when they might use it.

The use of TLS proxies to intercept encrypted traffic is controversial since the same mechanism can be used for both benevolent purposes, such as protecting against malware, and for malicious purposes, such as identity theft or warrantless government surveillance. To understand the prevalence and uses of these proxies, we build a TLS proxy measurement tool and deploy it via a Google AdWords campaign. We generate 2.9 million certificate tests and find that 1 in 250 TLS connections are proxied. The majority of these proxies appear to be benevolent, however we identify over 1,000 cases where three malware products are using this technology nefariously. We also find numerous instances of negligent and duplicitous behavior, some of which degrade security for users without their knowledge.