Title

Access Permissions for Apple Watch Applications: A Study on Users' Perceptions

Source of Publication

Proceedings of the 2020 IEEE International Conference on Communications, Computing, Cybersecurity, and Informatics, CCCI 2020

Abstract

© 2020 IEEE. The pervasiveness and sheer ubiquity of wearables, such as smartwatches, has given rise to a myriad of privacy concerns. In this paper, we examine the privacy issues which arise from the permission requests framework on Apple wearables and explore how end user's perception of these can inform better and more inclusive privacy. We conduct an empirical study which explores issues pertaining to data protection, safety, trust, ethics, and cybersecurity. We conducted two Amazon Mechanical Turk studies that investigate users' perception on app permission requests for different smartwatch applications. Our findings suggest that most users lack proper understanding of the cybersecurity risks posed and were unable to construe the rationale for permissions requests for popular smartwatch applications. Furthermore, the respondents believed that app developers might misuse their data, thereby, indicating lack of trust towards these app development enterprises. The respondents also believe that the application development companies should be held accountable for their alleged involvement in data breaches and privacy issues. Further, the majority of survey respondents indicated having some unease towards data usage policies of developers. Moreover, respondents consider all common types of private data (location, health and fitness, photos etc.) susceptible to some level of data breach. Lastly, our results indicate that the study participants experienced confusion in the 'usability' versus 'security' conundrum-while a bare majority of the users wanted ease of access, a similar minority preferred a higher level of security. We conclude by presenting a discussion to the quandaries that can help us interweave towards reliable, secure, trustworthy, and ethical technologies.

Document Type

Conference Proceeding

ISBN

9781728120355

Publisher

IEEE

Publication Date

11-3-2020

DOI

10.1109/ccci49893.2020.9256714

Scopus ID

85097832011

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