Defining Privacy: How Users Interpret Technical Terms in Privacy Policies

Tang, Jenny; Shoemaker, Hannah; Lerner, Ada; Birrell, Eleanor

doi:10.2478/popets-2021-0038

Cited by 23 publications

(13 citation statements)

References 29 publications

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“…Another limitation of study is that our sample is not US representative and includes more technology friendly, educated and young participants. However, despite these limitations, our sample represents the current smart home user population and Mechanical Turk population’s perceptions are US representative as shown by recent literature (Tang et al , 2022). Future studies could target a US representative population.…”

Section: Discussionmentioning

confidence: 99%

Enhancing the design of data-related privacy controls for smart home devices

Chhetri

Motti

2023

ICS

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Purpose Past research shows that users of smart home devices (SHDs) have privacy concerns. These concerns have been validated from technical research that shows SHDs introduce a lot of privacy risks. However, there is limited research in addressing these concerns and risks. This paper aims to bridge this gap by informing the design of data-related privacy controls for SHDs. Design/methodology/approach In this paper, the authors follow a user-centered design approach to design data-related privacy controls from design requirements backed by literature. The authors test the design for usability and perceived information control using psychometrically validated scales. For this purpose, two variations of the prototype (MyCam1 with a listing of data-related privacy controls and MyCam2 with three privacy presets) were created and tested them in a between-subjects experimental setting. Study participants (n = 207) were recruited via Mechanical Turk and asked to use the prototype app. An online survey was distributed to the participants to measure some usability and privacy-related constructs. Findings Findings show that the presented prototype designs were usable and met the privacy control needs of users. The prototype design with privacy presets (MyCam2) was found to be significantly more usable than the list of privacy controls (MyCam1). Originality The findings of this paper are original and build on the paper presented at the International Symposium on Human Aspects of Information Security and Assurance (HAISA 2022). This paper contributes improved and usable designs of privacy controls for smart home applications.

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Section: Discussionmentioning

confidence: 99%

Enhancing the design of data-related privacy controls for smart home devices

Chhetri

Motti

2023

ICS

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“…Our study has limitations that are typical of user studies. For one, participants on crowdsourcing platforms are typically younger, more educated, and more technologically savvy than the general population [4,17,18,29,30]. Additionally, participants may have been biased in their responses due to social desirability (e.g., attempting to provide likable answers) or demand effects (i.e., inferring a study purpose when responding) [31,32].…”

Section: Limitationsmentioning

confidence: 99%

Contextualizing Interpersonal Data Sharing in Smart Homes

He,

Reitinger,

Almogbil

et al. 2024

PoPETs

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A key feature of smart home devices is monitoring the environment and recording data. These devices provide security via motion-detection video alerts, cost-savings via thermostat usage history, and peace of mind via functions like auto-locking doors or water leak detectors. At the same time, the sharing of this information in interpersonal relationships---though necessary---is currently accomplished on an all-or-nothing basis. This can easily lead to oversharing in a multi-user environment. Although prior work has studied people's perceptions of information sharing with vendors or ISPs, the sharing of household data among users who interact personally is less well understood. Interpersonal situations make data sharing much more context-based and, thus, more complicated. In this paper, we use themes from the theory of contextual integrity in an online survey (n=1,992) to study how people perceive data sharing with others in smart homes and inform future designs and research. Our results show that data recipients in a smart home can be reduced to three major groups, and data types matter more than device types. We also found that the types of access control desired by users can vary from scenario to scenario. Depending on whom they are sharing data with and about what data, participants expressed varying levels of comfort when presented with different types of access control (e.g., explicit approval versus time-limited access). Taken together, this provides strong evidence that a more dynamic access control system is needed, and we can design it in a more usable way.

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“…According to this vision, the DPO advising task is "driven by research. " For example, Tang et al 14 find that users have difficulties understanding the technical terms used in privacy policies because they misunderstand and misconstrue them. As a result, privacy policies themselves are misunderstood and misinterpreted.…”

Section: Usable Security and Privacy For Security And Privacy Workersmentioning

confidence: 99%