Usable Privacy Research Articles

StyleAdv: A Usable Privacy Framework Against Facial Recognition with Adversarial Image Editing

In this era of ubiquitous surveillance and online presence, protecting facial privacy has become a critical concern for individuals and society as a whole. Adversarial attacks have emerged as a promising solution to this problem, but current methods are limited in quality or are impractical for sensitive domains such as facial editing. This paper presents a novel adversarial image editing framework called StyleAdv, which leverages StyleGAN's latent spaces to generate powerful adversarial images, providing an effective tool against facial recognition systems. StyleAdv achieves high success rates by employing meaningful facial editing with StyleGAN while maintaining image quality, addressing a challenge faced by existing methods. To do so, the comprehensive framework integrates semantic editing, adversarial attacks, and face recognition systems, providing a cohesive and robust tool for privacy protection. We also introduce the ``residual attack`` strategy, using residual information to enhance attack success rates. Our evaluation offers insights into effective editing, discussing tradeoffs in latent spaces, optimal edits for our optimizer, and the impact of utilizing residual information. Our approach is transferable to state-of-the-art facial recognition systems, making it a versatile tool for privacy protection. In addition, we provide a user-friendly interface with multiple editing options to help users create effective adversarial images. Extensive experiments are used to provide insights and demonstrate that StyleAdv outperforms state-of-the-art methods in terms of both attack success rate and image quality. By providing a versatile tool for generating high-quality adversarial samples, StyleAdv can be used both to enhance individual users' privacy and to stimulate advances in adversarial attack and defense research.

Structural and functional explanations for informing lay and expert users: the case of functional encryption

Usable explanations of privacy-enhancing technologies (PETs) help users make more informed privacy decisions, but the explanations of PETs are generally geared toward individuals with more technical knowledge. To explain functional encryption (FE) to experts and laypersons, we investigate structural and functional explanations and explore users' interests and preferences, as well as how they affect users' comprehension and decisions about sharing data. To this end (with an EU-based population), we conducted four focus groups, in combination with walk-throughs, with 13 participants in the first study, followed by an online survey with 347 experts and 370 laypersons. Both explanations were considered useful in fulfilling the different needs of participants interested in the privacy policy information. Participants, regardless of their expertise, trusted and were more satisfied with the structural explanation. However, functional explanations had a higher contribution to all participants' comprehension. We, therefore, recommend combining both types of explanations for a usable privacy policy.

An Empirical Analysis of E-Governments’ Cookie Interfaces in 50 Countries

Cookies have been used by websites to store information about user behavior. Although they provide several benefits, including improving user experience, they can threaten user privacy, particularly when websites use third-party cookies for data analysis. Websites must inform their users about what data are collected and how they are used through the cookie interface. Thus, it is important to understand the effects of cookie interface design on user behavior to verify whether these interfaces provide users with the required information to make an informed decision. In this paper, we evaluated the cookie interfaces of 243 E-Government websites based on well-defined guidelines to understand the critical factors designers should consider when designing cookie interfaces. To evaluate the cookies interfaces’ usability, we selected one of the inspection-based methods called the individual expert review method. The results showed that European websites are more compliant with the adopted guidelines. Surprisingly, more than 50% of the websites did not provide a cookie interface to their users, while more than 40% did not provide a privacy policy. The primary finding of this study is that over 90% of the websites use dark patterns in their interfaces. The study concludes with some recommendations to help in designing a usable privacy interface.

Privacy explanations – A means to end-user trust

Software systems are ubiquitous, and their use is ingrained in our everyday lives. They enable us to get in touch with people quickly and easily, support us in gathering information, and help us perform our daily tasks. In return, we provide these systems with a large amount of personal information, often unaware that this is jeopardizing our privacy. End users are typically unaware of what data is collected, for what purpose, who has access to it, and where and how it is stored. To address this issue, we looked into how explainability might help to tackle this problem. We created privacy explanations that aim to help to clarify to end users why and for what purposes specific data is required. We asked end users about privacy explanations in a survey and found that the majority of respondents (91.6 %) are generally interested in receiving privacy explanations. Our findings reveal that privacy explanations can be an important step towards increasing trust in software systems and can increase the privacy awareness of end users. These findings are a significant step in developing privacy-aware systems and incorporating usable privacy features into them, assisting users in protecting their privacy.

Toward Dynamic Consent for Privacy-Aware Pervasive Health and Well-being: A Scoping Review and Research Directions

Recent advances in sensor-enabled services have facilitated the use of mobile, wearable, and IoT devices; for example, an extensive range of sensor data are used to automatically track symptoms and diagnose health and well-being status of an individual (e.g., depression). As personal data are being continuously and unobtrusively sensed and collected at large scale, this raises privacy concerns in certain contexts (e.g., GPS data collection at privacy-sensitive places). Current one-off informed consent in such pervasive sensing scenarios does not offer context-awareness support that enables selective data disclosure based on a user’s needs or preferences (e.g., disabling GPS data collection when visiting hospitals). A lack of context-awareness support in informed consent would be a critical barrier to user acceptance of data-intensive pervasive computing for health and well-being. As an alternative method, we introduce the concept of “dynamic consent,” a type of informed consent that enables granular data consent and management, initially introduced in biomedical research for patient data management. We explore how this consent practice within biomedical research might inform usable privacy designs in pervasive computing by conducting a scoping review of dynamic consent literature and discussing future research directions.

Capturing drivers’ privacy preferences for intelligent transportation systems: An intercultural perspective

While recent research on intelligent transportation systems including vehicular communication systems has focused on technical aspects, little research work has been conducted on drivers’ privacy perceptions and preferences. Understanding the driver’s privacy perceptions and preferences will allow researchers to design usable privacy and identity management systems offering user privacy choices and controls for intelligent transportation systems. We conducted in-depth semi-structured interviews with 17 Swedish drivers to analyse their privacy perceptions and preferences for intelligent transportation systems, particularly for user control and for privacy trade-offs with cost, safety and usability. We also compare our results from the interviews with Swedish drivers with results from interviews that we conducted previously with South African drivers. Our cross-cultural comparison shows that perceived privacy implications, the drivers’ willingness to share location information under certain conditions with other parties, as well as their appreciation of Privacy Enhancing Technologies differ significantly across drivers with different cultural backgrounds. We further discuss the cultural impact on privacy preferences, including those for privacy trade-offs, and the implications of our results for usable privacy-enhancing Identity Management for future vehicular communication systems. In particular, we provide recommendations for suitable pre-defined privacy options to be offered to users with different cultural backgrounds enabling them to easily make privacy-related control choices.

Finding, getting and understanding: the user journey for the GDPR’S right to access

ABSTRACT In both data protection law and research of usable privacy, awareness and control over the collection and use of personal data are understood to be cornerstones of digital sovereignty. For example, the European General Data Protection Regulation (GDPR) provides data subjects with the right to access data collected by organisations but remains unclear on the concrete process design. However, the design of data subject rights is crucial when it comes to the ability of customers to exercise their right and fulfil regulatory aims such as transparency. To learn more about user needs in implementing the right to access as per GDPR, we conducted a two-step study. First, we defined a five-phase user experience journey regarding the right to access: finding, authentication, request, access and data use. Second, and based on this model, 59 participants exercised their right to access and evaluated the usability of each phase. Drawing on 422 datasets spanning 139 organisations, our results show several interdependencies of process design and user satisfaction. Thereby, our insights inform the community of usable privacy and especially the design of the right to access with a first, yet robust, empirical body.

A Taxonomy of user-perceived privacy risks to foster accountability of data-based services

Data protection risks play a major role in data protection laws and have shown to be suitable means for accountability in designing for usable privacy. Especially in the legal realm, risks are typically collected heuristically or deductively, e.g., by referring to fundamental right violations. Following a user-centered design credo, research on usable privacy has shown that a user-perspective on privacy risks can enhance system intelligibility and accountability. However, research on mapping the landscape of user-perceived privacy risks is still in its infancy. To extend the corpus of privacy risks as users perceive them in their daily use of technology, we conducted 9 workshops collecting 91 risks in the fields of web browsing, voice assistants and connected mobility. The body of risks was then categorized by 11 experts from the legal and HCI-domain. We find that, while existing taxonomies generally fit well, a societal dimension of risks is not yet represented. Discussing our empirically backed taxonomy including the full list of 91 risks, we demonstrate roads to use user-perceived risks as a mechanism to foster accountability for usable privacy in connected devices.

Privacy and Safety on Social Networking Sites: Autistic and Non-Autistic Teenagers’ Attitudes and Behaviors

Autistic teenagers are suspected to be more vulnerable to privacy and safety threats on social networking sites (SNS) than the general population. However, there are no studies comparing these users’ privacy and safety concerns and protective strategies online with those reported by non-autistic teenagers. Furthermore, researchers have yet to identify possible explanations for autistic teenagers’ increased risk of online harms. To address these research gaps, we conducted semi-structured interviews with 12 autistic and 16 non-autistic teenagers assessing their privacy- and safety-related attitudes and behaviors on SNS, and factors affecting them. We used videos demonstrating relevant SNS scenarios as prompts to engage participants in conversation. Through our thematic analyses, we found evidence that autistic teenagers may be more averse to taking risks on SNS than non-autistic teenagers. Yet, several personal, social, and SNS design factors may make autistic teenagers more vulnerable to cyberbullying and social exclusion online. We provide recommendations for making SNS safer for autistic teenagers. Our research highlights the need for more inclusive usable privacy and security research with this population.

Complex, but in a good way? How to represent encryption to non-experts through text and visuals – Evidence from expert co-creation and a vignette experiment

An ongoing discussion in the field of usable privacy and security debates whether security mechanisms should be visible to end-users during interactions with technology, or hidden away. This paper addresses this question using a mixed-methods approach, focusing on encryption as a mechanism for confidentiality during data transmission on a smartphone application. In study 1, we conducted a qualitative co-creation study with security and Human-Computer Interaction (HCI) experts (N = 9) to create appropriate textual and visual representations of the security mechanism encryption in data transmission. We investigated this question in two contexts: online banking and e-voting. In study 2, we put these ideas to the test by presenting these visual and textual representations to non-expert users in an online vignette experiment (N = 2180). We found a statistically significant and positive effect of the textual representation of encryption on perceived security and understanding, but not on user experience (UX). More complex text describing encryption resulted in higher perceived security and more accurate understanding. The visual representation of encryption had no statistically significant effect on perceived security, UX or understanding. Our study contributes to the larger discussion regarding visible instances of security and their impact on user perceptions.

A Systematic Literature Review of Empirical Methods and Risk Representation in Usable Privacy and Security Research

Usable privacy and security researchers have developed a variety of approaches to represent risk to research participants. To understand how these approaches are used and when each might be most appropriate, we conducted a systematic literature review of methods used in security and privacy studies with human participants. From a sample of 633 papers published at five top conferences between 2014 and 2018 that included keywords related to both security/privacy and usability, we systematically selected and analyzed 284 full-length papers that included human subjects studies. Our analysis focused on study methods; risk representation; the use of prototypes, scenarios, and educational intervention; the use of deception to simulate risk; and types of participants. We discuss benefits and shortcomings of the methods, and identify key methodological, ethical, and research challenges when representing and assessing security and privacy risk. We also provide guidelines for the reporting of user studies in security and privacy.

Prototyping Usable Privacy and Security Systems: Insights from Experts

ABSTRACT Iterative design, implementation, and evaluation of prototype systems is a common approach in Human-Computer Interaction (HCI) and Usable Privacy and Security (USEC); however, research involving physical prototypes can be particularly challenging. We report on twelve interviews with established and nascent USEC researchers who prototype security and privacy-protecting systems and have published work in top-tier venues. Our interviewees range from professors to senior PhD candidates, and researchers from industry. We discussed their experiences conducting USEC research that involves prototyping, opinions on the challenges involved, and the ecological validity issues surrounding current evaluation approaches. We identify the challenges faced by researchers in this area such as the high costs of conducting field studies when evaluating hardware prototypes, the scarcity of open-source material, and the resistance to novel prototypes. We conclude with a discussion of how the USEC community currently supports researchers in overcoming these challenges and places to potentially improve support.

Exploring mental models of the right to informational self-determination of office workers in Germany

AbstractApplied privacy research has so far focused mainly on consumer relations in private life. Privacy in the context of employment relationships is less well studied, although it is subject to the same legal privacy framework in Europe. The European General Data Protection Regulation (GDPR) has strengthened employees’ right to privacy by obliging that employers provide transparency and intervention mechanisms. For such mechanisms to be effective, employees must have a sound understanding of their functions and value. We explored possible boundaries by conducting a semi-structured interview study with 27 office workers in Germany and elicited mental models of the right to informational self-determination, which is the European proxy for the right to privacy. We provide insights into (1) perceptions of different categories of data, (2) familiarity with the legal framework regarding expectations for privacy controls, and (3) awareness of data processing, data flow, safeguards, and threat models. We found that legal terms often used in privacy policies used to describe categories of data are misleading. We further identified three groups of mental models that differ in their privacy control requirements and willingness to accept restrictions on their privacy rights. We also found ignorance about actual data flow, processing, and safeguard implementation. Participants’ mindsets were shaped by their faith in organizational and technical measures to protect privacy. Employers and developers may benefit from our contributions by understanding the types of privacy controls desired by office workers and the challenges to be considered when conceptualizing and designing usable privacy protections in the workplace.

Usable Security and Privacy on Online Social Networks

Hundreds of millions of people use online social networks (OSNs), and this use is growing rapidly. On the one hand, users of OSNs have created accounts, which include their personal information, interests, associations, postings, daily activities, sharing of social media, and so forth. In addition, users want to protect these information and activities. But on the other hand, they want to use the services, which are provided by OSNs in order to stay in touch with others. Therefore, for achieving this desire, users reveal their personal information intentionally or accidentally. Why? Because users of OSNs do not have adequate information that helps them in making security and privacy decisions effectively in addition to inadequate feedback about the implications of user decisions. This means users do not know what to reveal and how. In order to cope with this problem, a systematic literature review of the usable security and privacy on OSNs was performed. This review is an attempt to pursue the contours of research in OSNs. Therefore, this paper discusses the existing research work, highlights the main research challenges and existing solutions, identifies open research issues, and proposes some directions for future research in the usable security and privacy on OSNs.

It Is About What They Could Do with the Data

Smart Meters are a key component of increasing the power efficiency of the Smart Grid. To help manage the grid effectively, these meters are designed to collect information on power consumption and send it to third parties. With Smart Metering, for the first time, these cloud-connected sensing devices are legally mandated to be installed in the homes of millions of people worldwide. Via a multi-staged empirical study that utilized an open-ended questionnaire, focus groups, and a design probe, we examined how people characterize the tension between the utility of Smart Metering and its impact on privacy. Our findings show that people seek to make abstract Smart Metering data accountable by connecting it to their everyday practices. Our insight can inform the design of usable privacy configuration tools that help Smart Metering consumers relate abstract data with the real-world implications of its disclosure.

Usable privacy and security

Usable privacy and security

Usability versus privacy instead of usable privacy

A smartphone is an indispensible device that also holds a great deal of personal and private data. Contact details, party or holiday photos and emails --- all carried around in our pockets and easily lost. On Android, the most widely-used smartphone operating system, access to this data is regulated by permissions. Apps request these permissions at installation, and they ideally only ask for permission to access data they really need to carry out their functions. The user is expected to check, and grant, requested permissions before installing the app. Their privacy can potentially be violated if they fail to check the permissions carefully. In June 2014 Google changed the Android permission screen, perhaps attempting to improve its usability. Does this mean that all is well in the Android eco-system, or was this update a retrograde move? This article discusses the new permission screen and its possible implications for smartphone owner privacy.

Usable Security: History, Themes, and Challenges

There has been roughly 15 years of research into approaches for aligning research in Human Computer Interaction with computer Security, more colloquially known as ``usable security.'' Although usability and security were once thought to be inherently antagonistic, today there is wide consensus that systems that are not usable will inevitably suffer security failures when they are deployed into the real world. Only by simultaneously addressing both usability and security concerns will we be able to build systems that are truly secure. This book presents the historical context of the work to date on usable security and privacy, creates a taxonomy for organizing that work, outlines current research objectives, presents lessons learned, and makes suggestions for future research. Table of Contents: Acknowledgments / Figure Credits / Introduction / A Brief History of Usable Privacy and Security Research / Major Themes in UPS Academic Research / Lessons Learned / Research Challenges / Conclusion: The Next Ten Years / Bibliography / Authors' Biographies

Reflections on U-PriSM 2

The Second Usable Privacy and Security for Mobile Devices Workshop (U-PriSM 2) was co-located with MobileHCI'13 in Munich, Germany. The U-PriSM 2 was an opportunity for researchers and practitioners to discuss research challenges and experiences around the usable privacy and security of mobile devices (smartphones and tablets). Security and privacy often involve having non-security experts, or even novice users, regularly making important decisions while their main focus is on other primary tasks. This is especially true for mobile devices where users can quickly and easily install apps, where user interfaces are minimal due to space constraints, and where users are often distracted by their environment. Likewise, mobile devices present unique privacy and security risks because they allow third-party applications access to personal information and sensor data. The amount and sensitivity of such personally identifying information is likely to increase as device functionality increases. The convergence of these factors means that improvements to security and privacy provisions on mobile devices are becoming increasingly important. Workshop participants had a chance to explore mobile device usage and the unique usable security and privacy challenges that arise, discuss proposed systems and ideas that address these needs, and work towards the development of design principles to inform future development in the area.

The Privacy Paradox: A Facebook Case Study

The utility of social networks is contingent on information sharing, which constrains privacy. Engaging in online social networks is seen to indicate that the participants either do not care about privacy, do not understand the risks of information sharing, or find privacy controls to be unusable. Given the contextual nature of privacy all three models may exist in the population and in fact in a single person. We introduce the three distinct academic threads leading to each model, i.e. rational economics, risk behavior, and human computer interaction. Further, we conduct a survey based study to elicit the relative strengths of these explanations for information sharing on Facebook (n=384). Our findings indicate that while all three explanations are relevant, their relative strengths are different. The perceived risk of sharing information is the most important determinant of privacy behaviors; to a lesser extent usability of privacy controls is important. Finally, privacy preferences is the least important factor; thus, the explanation that people don’t care is weakest explanation of the privacy paradox (on Facebook).We argue that Facebook should invest in both more usable privacy controls and awareness of those controls. In general better controls and more information increased information sharing and lowered the perceptions of risk, thereby aligning expressed attitudes with observed behaviors and addressing the paradox. We note that privacy risks behaviors are determined by dread risk and familiarity on Facebook, as for risks offline. Thus, Facebook privacy efforts should leverage prior research in risk communication offline. Specifically, risk averse behaviors can be encouraged if risk communication focuses on severe, catastrophic, and rare consequences of information sharing.