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Author:

Zhou, Yun (Zhou, Yun.) | Raake, Alexander (Raake, Alexander.) | Xu, Tao (Xu, Tao.) | Zhang, Xuyun (Zhang, Xuyun.)

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Abstract:

A common issue is that a large number of authorized apps use important and sensitive personal information without arousing users’ full awareness. Existing schemes for privacy protection on smartphones try to provide users with privacy settings to control privacy leakage. Privacy settings on smartphone are intended to inform users about risks of privacy leakage and let users take over control of smartphone. Therefore, it is essential to understand and measure how much users perceive and trust these settings. To this end, we design and conduct a fine-grained online survey with 222 respondents. We collect the demographics as well as users’ smartphone usage, covering not only participants’ basic background information like age, gender, job, but also time of smartphone use per day, respective importance and sensitivity level of personal data, and their smartphone OSs. In this paper, we investigate users’ current privacy perception and protection on smartphone in different groups, discussing participants’ responses to (1) Rating the importance and sensitivity of personal information; (2) Trust on existing privacy protection; (3) Perceived control on smartphone; (4) Frequency of searching privacy knowledge; (5) Concerns about manufacturer and third-party company’s behaviors on personal data and decision. © 2017, Springer International Publishing AG.

Keyword:

Background information Online surveys Personal information Privacy leakages Privacy protection Privacy Settings Sensitive personal informations Trust

Author Community:

  • [ 1 ] [Zhou, Yun]School of Education, Shaanxi Normal University, Xi’an; Shaanxi; 710062, China
  • [ 2 ] [Raake, Alexander]Audiovisual Technology Group, Institute for Media Technology, University of Technology Ilmenau, Ilmenau; 98693, Germany
  • [ 3 ] [Xu, Tao]School of Software and Microelectronics, Northwestern Polytechnical University, Xi’an; Shaanxi; 710072, China
  • [ 4 ] [Xu, Tao]State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an; Shaanxi; 710054, China
  • [ 5 ] [Zhang, Xuyun]Department of Electrical and Computer Engineering, University of Auckland, Auckland; 1010, New Zealand

Reprint Author's Address:

  • [Zhou, Yun]School of Education, Shaanxi Normal University, Xi’an; Shaanxi; 710062, China;;

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Source :

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISSN: 0302-9743

Year: 2017

Publish Date: 2017

Volume: 10581 LNCS

Page: 427-441

Language: English

0 . 4 0 2

JCR@2005

JCR Journal Grade:2

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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