Quantifying Users’ Beliefs about Software Updates (USEC ’18)

AbstractSoftware updates are critical to the performance, compatibility, and security of software systems. However, users do not always install updates, leaving their machines vulnerable to attackers’ exploits. While recent studies have highlighted numerous reasons why users ignore updates, little is known about how prevalent each of these beliefs is. Gaining a better understanding of the prevalence of each belief may help software designers better target their efforts in understanding what…

Contextualizing Privacy Decisions for Better Prediction (and Protection) (CHI ’18)

Abstract Modern mobile operating systems implement an ask-on-first-use policy to regulate applications’ access to private user data: the user is prompted to allow or deny access to a sensitive resource the first time an app attempts to use it. Prior research shows that this model may not adequately capture user privacy preferences because subsequent requests may occur under varying contexts. To address this shortcoming, we implemented a novel privacy management…

An Experience Sampling Study of User Reactions to Browser Warnings in the Field (CHI ’18)

Abstract 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…

A Usability Evaluation of Tor Launcher (PETS ’17)

Abstract Although Tor has state-of-the art anti-censorship measures, users in heavily censored environments will likely not be able to connect to Tor because they cannot make the correct decisions during the configuration process. We perform the first usability evaluation of Tor Launcher, the graphical user interface (GUI) that Tor Browser uses to configure connections to Tor. Our study shows that 79% (363 of 458) of user attempts to connect to…

Let’s Go in for a Closer Look: Observing Passwords in Their Natural Habitat (CCS ’17)

Abstract Text passwords—a frequent vector for account compromise, yet still ubiquitous—have been studied for decades by researchers attempting to determine how to coerce users to create passwords that are hard for attackers to guess but still easy for users to type and memorize. Most studies examine one password or a small number of passwords per user, and studies often rely on passwords created solely for the purpose of the study…

TurtleGuard: Helping Android Users Apply Contextual Privacy Preferences (SOUPS ’17)

Abstract Current mobile platforms provide privacy management interfaces to regulate how applications access sensitive data. Prior research has shown how these interfaces are insufficient from a usability standpoint: they do not account for context. In allowing for more contextual decisions, machine-learning techniques have shown great promise for designing systems that automatically make privacy decisions on behalf of the user. However, if such decisions are made automatically, then feedback mechanisms are…

The Feasibility of Dynamically Granted Permissions: Aligning Mobile Privacy with User Preferences (Oakland ’17)

Abstract Current smartphone operating systems regulate application permissions by prompting users on an ask-on-first-use basis. Prior research has shown that this method is ineffective because it fails to account for context: the circumstances under which an application first requests access to data may be vastly different than the circumstances under which it subsequently requests access. We performed a longitudinal 131-person field study to analyze the contextuality behind user privacy decisions…

Personalized Security Messaging: Nudges for Compliance with Browser Warnings (EuroUSEC ’17)

Abstract Decades of psychology and decision-making research show that everyone makes decisions differently; yet security messaging is still one-size-fits-all. This suggests that we can improve outcomes by delivering information relevant to how each individual makes decisions. We tested this hypothesis by designing messaging customized for stable personality traits—specifically, the five dimensions of the General Decision-Making Style (GDMS) instrument. We applied this messaging to browser warnings, security messaging encountered by millions…

“Is Our Children’s Apps Learning?” Automatically Detecting COPPA Violations (ConPro ’17)

Abstract In recent years, a market of games and learning apps for children has flourished in the mobile world. Many of these often “free” mobile apps have access to a variety of sensitive personal information about the user, which app developers can monetize via advertising or other means. In the United States, the Children’s Online Privacy Protection Act (COPPA) protects children’s privacy, requiring parental consent to the use of personal…

The Teaching Privacy Curriculum (SIGCSE ’16)

Abstract A basic understanding of online privacy is essential to being an informed digital citizen, and therefore basic privacy education is becoming ever more necessary. Recently released high school and college computer science curricula acknowledge the significantly increased importance of fundamental knowledge about privacy, but do not yet provide concrete content in the area. To address this need, over the past two years, we have developed the Teaching Privacy Project…