Smart-home automations enable users to customize smart devices to react automatically to people, the environment, and more. For example, an automation might adjust the lights when people are at home or enable a garage door to open by voice command. While automations offer convenience and accessibility, they can also inadvertently expose users to security and privacy risks, such as leaking sensitive data or allowing untrusted parties to control users' devices. Prior work has shown that information flow analysis is a promising technique for identifying these kinds of risks, hypothesizing that the analysis would be yet more effective if it could differentiate between devices located in different places in the home. We tested this hypothesis by developing a tool that extends prior information flow analysis approaches to account for device location. We conducted an interview study with 22 participants to build a dataset of home automations to establish a ground truth to evaluate the tool. We found that incorporating device location leads to an improved analysis that identifies more of the vulnerabilities users care about (F1 score 0.74) compared to prior work (F1 score 0.29). Our results demonstrate the feasibility of incorporating device location into an information flow analysis and, perhaps more importantly, suggest additional ways to prevent security and privacy risks beyond controlling potentially unsafe information flows.

Targeted online advertising is a well-known but extremely opaque phenomenon. Though the targeting capabilities of the ad tech ecosystem are public knowledge, from an outside perspective, it is difficult to measure and quantify ad targeting at scale. To shed light on the extent of targeted advertising on the web today, we conducted a controlled field measurement study of the ads shown to a representative sample of 286 participants in the U.S. Using a browser extension, we collected data on ads seen by users on 10 popular websites, including the topic of the ad, the value of the bid placed by the advertiser (via header bidding), and participants' perceptions of targeting. We analyzed how ads were targeted across individuals, websites, and demographic groups, how those factors affected the amount advertisers bid, and how those results correlated with participants' perceptions of targeting. Among our findings, we observed that the primary factors that affected targeting and bid values were the website the ad appeared on and individual user profiles. Surprisingly, we found few differences in how advertisers target and bid across demographic groups. We also found that high outliers in bid values (10x higher than baseline) may be indicative of retargeting. Our measurements provide a rare in situ view of targeting and bidding across a diversity of users.

Online display advertising on websites is widely disliked by users, with many turning to ad blockers to avoid “bad” ads. Recent evidence suggests that today’s ads contain potentially problematic content, in addition to well-studied concerns about the privacy and intrusiveness of ads. However, we lack knowledge of which types of ad content users consider problematic and detrimental to their browsing experience. Our work bridges this gap: first, we create a taxonomy of 15 positive and negative user reactions to online advertising from a survey of 60 participants. Second, we characterize classes of online ad content that users dislike or find problematic, using a dataset of 500 ads crawled from popular websites, labeled by 1000 participants using our taxonomy. Among our findings, we report that users consider a substantial amount of ads on the web today to be clickbait, untrustworthy, or distasteful, including ads for software downloads, listicles, and health & supplements.

Online advertising can be used to mislead, deceive, and manipulate Internet users, and political advertising is no exception. In this paper, we present a measurement study of online advertising around the 2020 United States elections, with a focus on identifying dark patterns and other potentially problematic content in political advertising. We scraped ad content on 745 news and media websites from six geographic locations in the U.S. from September 2020 to January 2021, collecting 1.4 million ads. We perform a systematic qualitative analysis of political content in these ads, as well as a quantitative analysis of the distribution of political ads on different types of websites. Our findings reveal the widespread use of problematic tactics in political ads, such as bait-and-switch ads formatted as opinion polls to entice users to click, the use of political controversy by content farms for clickbait, and the more frequent occurrence of political ads on highly partisan news websites. We make policy recommendations for online political advertising, including greater scrutiny of non-official political ads and comprehensive standards across advertising platforms.

Email encryption tools remain underused, even by people who frequently conduct sensitive business over email, such as lawyers and journalists. Usable encrypted email has remained out of reach largely because key management and verification remain difficult. However, key management has evolved in the age of social media: Keybase is a service that allows users to cryptographically link public keys to their social media accounts (e.g., Twitter), enabling key trust without out-of-band communication. We design and prototype Confidante, an encrypted email client that uses Keybase for automatic key management. We conduct a user study with 15 people (8 U. S. lawyers and 7 U. S. journalists) to evaluate Confidante's design decisions. We find that users complete an encrypted email task more quickly and with fewer errors using Confidante than with an existing email encryption tool, and that many users report finding Confidante comparable to using ordinary email. However, we also find that lawyers and journalists have diverse operational constraints and threat models, and thus that there may not be a one-size-fits-all solution to usable encrypted email. We reflect on our findings — both specifically about Confidante and more generally about the needs and constraints of lawyers and journalists—to identify lessons and remaining security and usability challenges for encrypted email.