arXiv subjects

David G. Balash

Publications and source records attributed to David G. Balash.

7 recordsLinked to original sources

arXiv2025

Longitudinal Analysis of Privacy Labels in the Apple App Store

In December of 2020, Apple started to require app developers to self-report privacy label annotations on their apps indicating what data is collected and how it is used.To understand the adoption and shifts in privacy labels in the App Store, we collected nearly weekly snapshots of over 1.6 million apps for over a year (July 15, 2021 -- October 25, 2022) to understand the dynamics of privacy label ecosystem. Nearly two years after privacy labels launched, only 70.1% of apps have privacy labels, but we observed an increase of 28% during the measurement period. Privacy label adoption rates are mostly driven by new apps rather than older apps coming into compliance. Of apps with labels, 18.1% collect data used to track users, 38.1% collect data that is linked to a user identity, and 42.0% collect data that is not linked. A surprisingly large share (41.8%) of apps with labels indicate that they do not collect any data, and while we do not perform direct analysis of the apps to verify this claim, we observe that it is likely that many of these apps are choosing a Does Not Collect label due to being forced to select a label, rather than this being the true behavior of the app. Moreover, for apps that have assigned labels during the measurement period nearly all do not change their labels, and when they do, the new labels indicate more data collection than less. This suggests that privacy labels may be a ``set once'' mechanism for developers that may not actually provide users with the clarity needed to make informed privacy decisions.

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arXiv2024

Honesty is the Best Policy: On the Accuracy of Apple Privacy Labels Compared to Apps' Privacy Policies

Apple introduced privacy labels in Dec. 2020 as a way for developers to report the privacy behaviors of their apps. While Apple does not validate labels, they also require developers to provide a privacy policy, which offers an important comparison point. In this paper, we fine-tuned BERT-based language models to extract privacy policy features for 474,669 apps on the iOS App Store, comparing the output to the privacy labels. We identify discrepancies between the policies and the labels, particularly as they relate to data collected linked to users. We find that 228K apps' privacy policies may indicate data collection linked to users than what is reported in the privacy labels. More alarming, a large number (97%) of the apps with a Data Not Collected privacy label have a privacy policy indicating otherwise. We provide insights into potential sources for discrepancies, including the use of templates and confusion around Apple's definitions and requirements. These results suggest that significant work is still needed to help developers more accurately label their apps. Our system can be incorporated as a first-order check to inform developers when privacy labels are possibly misapplied.

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arXiv2023

How Does Connecting Online Activities to Advertising Inferences Impact Privacy Perceptions?

Data dashboards are designed to help users manage data collected about them. However, prior work showed that exposure to some dashboards, notably Google's My Activity dashboard, results in significant decreases in perceived concern and increases in perceived benefit from data collection, contrary to expectations. We theorize that this result is due to the fact that data dashboards currently do not sufficiently "connect the dots" of the data food chain, that is, by connecting data collection with the use of that data. To evaluate this, we designed a study where participants assigned advertising interest labels to their own real activities, effectively acting as a behavioral advertising engine to "connect the dots." When comparing pre- and post-labeling task responses, we find no significant difference in concern with Google's data collection practices, which indicates that participants' priors are maintained after more exposure to the data food chain (differing from prior work), suggesting that data dashboards that offer deeper perspectives of how data collection is used have potential. However, these gains are offset when participants are exposed to their true interest labels inferred by Google. Concern for data collection dropped significantly as participants viewed Google's labeling as generic compared to their own more specific labeling. This presents a possible new paradox that must be overcome when designing data dashboards, the generic paradox, which occurs when users misalign individual, generic inferences from collected data as benign compared to the totality and specificity of many generic inferences made about them.

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arXiv2023

Educators' Perspectives of Using (or Not Using) Online Exam Proctoring

The onset of the COVID-19 pandemic changed the landscape of education and led to increased usage of remote proctoring tools that are designed to monitor students when they take assessments outside the classroom. While prior work has explored students' privacy and security concerns regarding online proctoring tools, the perspective of educators is under explored. Notably, educators are the decision makers in the classrooms and choose which remote proctoring services and the level of observations they deem appropriate. To explore how educators balance the security and privacy of their students with the requirements of remote exams, we sent survey requests to over 3,400 instructors at a large private university that taught online classes during the 2020/21 academic year. We had n=125 responses: 21% of the educators surveyed used online exam proctoring services during the remote learning period, and of those, 35% plan to continue using the tools even when there is a full return to in-person learning. Educators who use exam proctoring services are often comfortable with their monitoring capabilities. However, educators are concerned about students sharing certain types of information with exam proctoring companies, particularly when proctoring services collect identifiable information to validate students' identities. Our results suggest that many educators developed alternative assessments that did not require online proctoring and that those who did use online proctoring services often considered the tradeoffs between the potential risks to student privacy and the utility or necessity of exam proctoring services.

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arXiv2021

Security and Privacy Perceptions of Third-Party Application Access for Google Accounts (Extended Version)

Online services like Google provide a variety of application programming interfaces (APIs). These online APIs enable authenticated third-party services and applications (apps) to access a user's account data for tasks such as single sign-on (SSO), calendar integration, and sending email on behalf of the user, among others. Despite their prevalence, API access could pose significant privacy and security risks, where a third-party could have unexpected privileges to a user's account. To gauge users' perceptions and concerns regarding third-party apps that integrate with online APIs, we performed a multi-part online survey of Google users. First, we asked n = 432 participants to recall if and when they allowed third-party access to their Google account: 89% recalled using at least one SSO and 52% remembered at least one third-party app. In the second survey, we re-recruited n = 214 participants to ask about specific apps and SSOs they've authorized on their own Google accounts. We collected in-the-wild data about users' actual SSOs and authorized apps: 86% used Google SSO on at least one service, and 67% had at least one third-party app authorized. After examining their apps and SSOs, participants expressed the most concern about access to personal information like email addresses and other publicly shared info. However, participants were less concerned with broader -- and perhaps more invasive -- access to calendars, emails, or cloud storage (as needed by third-party apps). This discrepancy may be due in part to trust transference to apps that integrate with Google, forming an implied partnership. Our results suggest opportunities for design improvements to the current third-party management tools offered by Google; for example, tracking recent access, automatically revoking access due to app disuse, and providing permission controls.

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arXiv2021

Examining the Examiners: Students' Privacy and Security Perceptions of Online Proctoring Services

In response to the Covid-19 pandemic, educational institutions quickly transitioned to remote learning. The problem of how to perform student assessment in an online environment has become increasingly relevant, leading many institutions and educators to turn to online proctoring services to administer remote exams. These services employ various student monitoring methods to curb cheating, including restricted ("lockdown") browser modes, video/screen monitoring, local network traffic analysis, and eye tracking. In this paper, we explore the security and privacy perceptions of the student test-takers being proctored. We analyze user reviews of proctoring services' browser extensions and subsequently perform an online survey (n=102). Our findings indicate that participants are concerned about both the amount and the personal nature of the information shared with the exam proctoring companies. However, many participants also recognize a trade-off between pandemic safety concerns and the arguably invasive means by which proctoring services ensure exam integrity. Our findings also suggest that institutional power dynamics and students' trust in their institutions may dissuade students' opposition to remote proctoring.

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arXiv2021

Are Privacy Dashboards Good for End Users? Evaluating User Perceptions and Reactions to Google's My Activity (Extended Version)

Privacy dashboards and transparency tools help users review and manage the data collected about them online. Since 2016, Google has offered such a tool, My Activity, which allows users to review and delete their activity data from Google services. We conducted an online survey with $n = 153$ participants to understand if Google's My Activity, as an example of a privacy transparency tool, increases or decreases end-users' concerns and benefits regarding data collection. While most participants were aware of Google's data collection, the volume and detail was surprising, but after exposure to My Activity, participants were significantly more likely to be both less concerned about data collection and to view data collection more beneficially. Only $25\,\%$ indicated that they would change any settings in the My Activity service or change any behaviors. This suggests that privacy transparency tools are quite beneficial for online services as they garner trust with their users and improve their perceptions without necessarily changing users' behaviors. At the same time, though, it remains unclear if such transparency tools actually improve end user privacy by sufficiently assisting or motivating users to change or review data collection settings.

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