January 2025
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1 Read
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January 2025
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1 Read
November 2024
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21 Reads
Health-related data (HRD) about individuals are increasingly generated and processed. The sources and volume of such data have grown larger over the past years, they include wearable devices, health-related mobile apps, and electronic health records. HRD are sensitive, have important privacy implications, hence hold a special status under existing privacy laws and regulations. In this work, we focus on shadow HRD: these HRD are generated and/or processed by individuals by using general-purpose digital tools outside of a professional healthcare information system. Some examples are health-related queries made by individuals on general-purpose search engines and LLM-based chatbots, or medical appointments and contact information of health professionals synced to the cloud. Such data, and the privacy risks stemming from them, are often overlooked when studying digital health. Using information from two focus group sessions (23 participants in total), we identified and categorized a broad variety of user behaviors that, including the aforementioned examples, lead to the creation of shadow HRD. Then, informed by this categorization, we designed a questionnaire and deployed it through an online survey (300 respondents) to assess the prevalence of such behaviors among the general public, as well as user awareness of (and concerns about) the privacy risks stemming from their shadow HRD. Our findings show that most respondents adopt numerous and diverse behaviors that create shadow HRD, and that very few resort to mechanisms to protect their privacy.
July 2024
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43 Reads
Proceedings on Privacy Enhancing Technologies
Wearable activity trackers (WATs) have recently gained worldwide popularity, with over a billion devices collecting a range of personal data. To receive additional services, users commonly share this data with third-party applications (TPAs). However, this practice poses potential privacy risks. Privacy-enhancing technologies have been developed to address these concerns, but they often lack user-centered design, and therefore, are less likely to be directly related to users’ concerns and to be widely adopted. This study takes a participatory design approach involving 𝑁 = 26 experienced WAT users who share data with TPAs. Through a series of design sessions, participants conceptualized 19 solutions, from which we identified seven different design features. We further analyze and discuss how these features can be combined to assist users in managing their data sharing with TPAs and, therefore, enhancing their privacy. Finally, we selected the three most promising features, namely partial sharing, reminder, and revocation assistance, and conducted an online survey with 𝑁 = 201 WAT users to better understand the potential effectiveness and usability of these features. This work makes an important contribution by offering user-centered solutions and valuable insights for integrating privacy-enhancing technologies into the WAT ecosystem.
May 2024
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14 Reads
May 2024
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19 Reads
ACM Transactions on the Web
Internet users possess accounts on dozens of online services where they are often identified by one of their e-mail addresses. They often use the same address on multiple services and for communicating with their contacts. In this paper, we investigate attacks that enable an adversary (e.g., company, friend) to determine (stealthily or not) whether an individual, identified by their e-mail address, has an account on certain services (i.e., an account enumeration attack ). Such attacks on account privacy have serious implications as information about one’s accounts can be used to (1) profile them and (2) improve the effectiveness of phishing. We take a multifaceted approach and study these attacks through a combination of experiments (63 services), surveys (318 respondents), and focus groups (13 participants). We demonstrate the high vulnerability of popular services (93.7%) and the concerns of users about their account privacy, as well as their increased susceptibility to phishing e-mails that impersonate services on which they have an account. We also provide findings on the challenges in implementing countermeasures for service providers and on users’ ideas for enhancing their account privacy. Finally, our interaction with national data protection authorities led to the inclusion of recommendations in their developers’ guide.
April 2024
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101 Reads
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2 Citations
Proceedings on Privacy Enhancing Technologies
Second-hand electronic devices are increasingly being sold online. Although more affordable and more environment-friendly than new products, second-hand devices, in particular those with storage capabilities, create security and privacy threats (e.g., malware or confidential data still stored on the device, aka remnant data). Previous work studied this issue from a technical point of view or only from the perspective of the sellers of the devices, but the perspective of the buyers has been largely overlooked. In this paper, we fill this gap and take a multi-disciplinary approach, focusing on the case of Switzerland. First, we conduct a brief legal analysis of the rights and obligations related to second-hand storage devices. Second, in order to understand the buyers' practices related to these devices and their beliefs about their legal rights and obligations, we deploy a survey in collaboration with a major online platform for transactions of second-hand goods. We demonstrate that the risks highlighted in prior research might not materialize, as many buyers do not inspect the content of the bought devices (e.g., they format it directly). We also found that none of the buyers uses forensic techniques. We identified that the buyers' decisions about remnant data depend on the type of data. For instance, for data with illegal content, they would keep the data to report it to the authorities, whereas for sensitive personal data they would either delete the data or contact the sellers. We identified several discrepancies between the actual legal rights/obligations and users' beliefs.
February 2024
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78 Reads
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12 Citations
ACM Computing Surveys
Over the past decade, wearable activity trackers (WATs) have become increasingly popular. However, despite many research studies in different fields (such as psychology, health, and design), few have sought to jointly examine the critical aspects of utility (i.e., benefits brought by these devices), privacy, and security (i.e., risks and vulnerabilities associated with them). To fill this gap, we reviewed 236 studies that researched the benefits of using WATs, the implications for the privacy of users of WATs, and the security vulnerabilities of these devices. Our survey revealed that these devices expose users to several threats. For example, WAT data can be mined to infer private information, such as the personality traits of the user. Whereas many works propose empirical findings about users’ privacy perceptions and their behaviors in relation to privacy, we found relatively few studies researching technologies to better protect users’ privacy with these devices. This survey contributes to systematizing knowledge on the utility, privacy, and security of WATs, shedding light on the state-of-the-art approaches with these devices, and discussing open research opportunities.
February 2024
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160 Reads
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4 Citations
Computers in Human Behavior
Wearable trackers are believed to enhance users' self-knowledge, but their impact on the relationship that people have with their own bodies is relatively unexplored. This study aims to shed light on the potential of physiological data collected by a commercial wearable activity tracker to influence how users relate with their own bodies, specifically their body awareness, body image, body consciousness, and body surveillance. Additionally, the study seeks to determine whether this change in body perception improves or worsens the users' relation with their own bodies. We recruited 321 first-time wearable users, including a control group. Participants in the experimental group (N = 225) completed a set of scales and questionnaires addressing body awareness and representations before and after wearing a Fitbit for four months, and 20 of them were further interviewed about their experience. The findings indicate that participants' overall view of their bodies was not influenced by the device. However, the Fitbit did increase the awareness of bodily sensations, particularly for women. Moreover, we describe how participants made sense of the data displayed by the Fitbit, which was also used as an emotion-regulation tool. These results can contribute to the understanding of the impact of self-tracking technologies on the users’ perceptions of their own body and provide insights for future research in this field.
October 2023
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81 Reads
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3 Citations
Wearable devices, such as wearable activity trackers (WATs),are increasing in popularity. Although they can help to im-prove one’s quality of life, they also raise serious privacyissues. One particularly sensitive type of information has re-cently attracted substantial attention, namely personality, asit provides a means to influence individuals (e.g., voters inthe Cambridge Analytica scandal). This paper presents thefirst empirical study to show a significant correlation betweenWAT data and personality traits (Big Five). We conduct anexperiment with 200+ participants. The ground truth wasestablished by using the NEO-PI-3 questionnaire. The par-ticipants’ step count, heart rate, battery level, activities, sleeptime, etc. were collected for four months. By following aprincipled machine-learning approach, the participants’ per-sonality privacy was quantified. Our results demonstrate thatWATs data brings valuable information to infer the openness,extraversion, and neuroticism personality traits. We furtherstudy the importance of the different features (i.e., data types)and found that step counts play a key role in the inference ofextraversion and neuroticism, while openness is more relatedto heart rate.
October 2023
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137 Reads
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3 Citations
Proceedings on Privacy Enhancing Technologies
Disclosing personal information significantly increases the likelihood of incidents of cyberbullying. This highlights the significance of investigating the relationships between various stakeholders in cyberbullying incidents. Our objective is to gain insight into the roles of the stakeholders, types, and typical paths of personal information in cyberbullying incidents. To achieve this, we conducted a large-scale survey with a representative sample of internet users from the United States and Nigeria (N = 1555). Our findings indicate that cyberbullying is often fueled by personal information that becomes known, directly or through social media, to other stakeholders. Cyberbullying incidents involve more than just attackers and victims; they can involve other stakeholders as third-parties 'disclosers' Both strangers and friends typically engage in such activities. Cyberbullying incidents are twice as common in Nigeria as in the United States. Our findings have implications for design, social-media literacy programs, and policy.
... Other studies focus on user attitudes towards health information exchange (HIE) [4,18,24,33,40,60], assessing patients' willingness to share data from their EHR for scientific research. Outside the clinical setting, a number of studies have evaluated users' behaviors, awareness, and concerns toward the use of off-the-shelf wearable devices (e.g., Fitbit) [1,2,21,36,43,66,69,77]. Findings from such studies are summarized in a recent literature survey [56], reporting that wearable device users exhibit low knowledge of how data from their wearables is processed, as well as low privacy concerns. Other studies investigated users' perceptions and attitudes toward mobile phone health apps [16,41,42,53,58]. ...
February 2024
ACM Computing Surveys
... However, implementing RMT in an ED population presents unique challenges, most notably the use of wearable devices that are commonly associated with fitness and diet tracking. Such technology has been shown to trigger, maintain and worsen ED symptomatology in clinical and non-clinical populations [87,88], mirrored in reluctance amongst individuals with an ED history to participate in RMT studies [89]. To understand how RMT can be safely integrated into ED research and clinical practice, we encourage future research to follow processes similar to those in STORY (e.g., PPI; close consultation with experts-by-experience; process evaluations). ...
February 2024
Computers in Human Behavior
... Due to their physiological (e.g., heart rate) and contextual (e.g., activities) nature, WAT data are highly sensitive and might raise various privacy issues. For instance, WAT data can be used to infer daily activities and habits (e.g., eating) [1,32,66,76], drug usage (e.g., cocaine) [78], SARS-CoV-2 infections [54], mental health [2], and even personality traits [114]. Aggregated location data have even been used to locate military bases and to infer their internal structures [53], specifically in remote areas where unusual activity patterns were observed. ...
October 2023
... A staggering 37.71% of respondents acknowledged disseminating such content without seeking authorization from the individual involved. This behavior not only portrays a severe breach of digital trust and privacy but also opens the door to a myriad of other harmful consequences such as depression, cyberbullying, low self-esteem, and suicidal thoughts Aliyu, Salehzadeh Niksirat, Huguenin and Cherubini (2023 Kraus which provides a comprehensive insight into the correlations between sexting behaviors and various mental health outcomes among college students in the United States. This study reveals that 58% of the participants engaged in sexting, a notable figure given Nigeria's conservative cultural backdrop. ...
October 2023
Proceedings on Privacy Enhancing Technologies
... Since it can handle both numerical and categorical data well and is a member of the supervised learning class of algorithms, DT is used to effectively solve classification problems [63]. Research works as in [64] and [65] show that DT can perform exceptionally well in tasks involving data classification. Moreover, DT comes with some built-in tools for managing the dataset's outliers. ...
June 2023
IEEE/ACM Transactions on Computational Biology and Bioinformatics
... In our study, participants expressed a clear preference for conversational agents that adopted a socially-oriented communication style over a blunt or robotic manner. To enhance the chatbot's conversational skills, relevant capabilities include generating neutral responses that facilitate thoughtful exchanges [91], structuring conversations to resolve conflicts and achieve consensus [49], and showing emotional intelligence to enhance human expressiveness [114] and self-reflection [57]. Advancement in large language models offers promise make responses more conversational and context-aware. ...
April 2023
Proceedings of the ACM on Human-Computer Interaction
... Several studies investigated privacy concerns and perceptions related to sharing medical data (cf. [4,13,32,37,51,65,74]). However, inconsistencies exist among these studies regarding the level of trust in researchers, the understanding of potential privacy risks and protection methods, and the effectiveness of the privacy measures in encouraging data sharing. ...
January 2023
Proceedings on Privacy Enhancing Technologies
... We consider HRD that are organized in a fixed format with well-defined fields as Structured, those that do not adhere to a fixed format yet contain markers (e.g., keywords, tags) indicating their content as Semi-structured, and those that lack formatting and organization as unstructured (e.g., untagged text or images). We also tagged HRD sources for which the HRD relates to individuals other than the one creating them (e.g., " Child's physician phone number in address book") with the Interdependent privacy tag [28][29][30][31]. Finally, we used the Far-fetched tag to indicate HRD sources that are either too futuristic (e.g., "Card that has your medical information which gives you access to hospital facilities automatically") or require a significant effort by an adversary to infer health-related information from (e.g., "Thermostat of smart homes can indicate health status"). ...
June 2022
... Examples include UP contributions that tangible privacy-preserving methods for smart homes [125] and PAS contributions that fully disable sensors from collecting data by cutting off power [26]. In "Better than Nothing" approaches [4,8,9,32,37,52,60,61,69,83,98,100,119,121,132,137], contributions identified that "All or Nothing" approaches come at the cost of long-term and continuous system performance (i.e., how effective can the system be in performing its duties if it is frequently disabled and re-enabled) in order to provide explicit guarantees of user comfort and privacy. Conversely, these works propose methods that balance these factors by utilizing sanitization (e.g., removing speech from acoustic information [60,132]) or granularity (e.g., reducing the resolution of images to reduce sensitive content [100,121]). ...
December 2021
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
... Participatory design is a user-centered approach designers use to incorporate end users into the design process [62]. This approach has been used in multiple studies related to utility, including WAT utility [22,69,72], and privacy [57,88]. It proves especially valuable in developing solutions related to usable security and privacy [116]. ...
June 2021