Privacy mechanisms for drones: Perceptions of drone controllers and bystanders

Yaxing Yao; Huichuan Xia; Yun Huang; Yang Wang

doi:10.1145/3025453.3025907

Privacy mechanisms for drones: Perceptions of drone controllers and bystanders

Yaxing Yao, Huichuan Xia, Yun Huang, Yang Wang

School of Information Studies

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

15 Scopus citations

Abstract

Drones pose privacy concerns such as surveillance and stalking. Many technology-based or policy-based mechanisms have been proposed to mitigate these concerns. However, it is unclear how drone controllers and bystanders perceive these mechanisms and whether people intend to adopt them. In this paper, we report results from two rounds of online survey with 169 drone controllers and 717 bystanders in the U.S. We identified respondents' perceived pros and cons of eight privacy mechanisms. We found that owner registration and automatic face blurring individually received most support from both controllers and bystanders. Our respondents also suggested using varied combinations of mechanisms under different drone usage scenarios, highlighting their context-dependent preferences. We outline a set of important questions for future privacy designs and public policies of drones. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

Original language	English (US)
Title of host publication	CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
Subtitle of host publication	Explore, Innovate, Inspire
Publisher	Association for Computing Machinery
Pages	6777-6788
Number of pages	12
Volume	2017-May
ISBN (Electronic)	9781450346559
DOIs	https://doi.org/10.1145/3025453.3025907
State	Published - May 2 2017
Event	2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017 - Denver, United States Duration: May 6 2017 → May 11 2017

Other

Other	2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017
Country	United States
City	Denver
Period	5/6/17 → 5/11/17

Keywords

Drone
Perceptions
Privacy mechanisms
UAS
UAV

ASJC Scopus subject areas

Human-Computer Interaction
Computer Graphics and Computer-Aided Design
Software

Access to Document

10.1145/3025453.3025907

Fingerprint Dive into the research topics of 'Privacy mechanisms for drones: Perceptions of drone controllers and bystanders'. Together they form a unique fingerprint.

Cite this

Privacy mechanisms for drones : Perceptions of drone controllers and bystanders. / Yao, Yaxing; Xia, Huichuan; Huang, Yun; Wang, Yang.

CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire. Vol. 2017-May Association for Computing Machinery, 2017. p. 6777-6788.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yao, Y, Xia, H, Huang, Y & Wang, Y 2017, Privacy mechanisms for drones: Perceptions of drone controllers and bystanders. in CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems: Explore, Innovate, Inspire. vol. 2017-May, Association for Computing Machinery, pp. 6777-6788, 2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017, Denver, United States, 5/6/17. https://doi.org/10.1145/3025453.3025907

@inproceedings{62ffebdae8714a5a83b0ed175e235bbf,

title = "Privacy mechanisms for drones: Perceptions of drone controllers and bystanders",

abstract = "Drones pose privacy concerns such as surveillance and stalking. Many technology-based or policy-based mechanisms have been proposed to mitigate these concerns. However, it is unclear how drone controllers and bystanders perceive these mechanisms and whether people intend to adopt them. In this paper, we report results from two rounds of online survey with 169 drone controllers and 717 bystanders in the U.S. We identified respondents' perceived pros and cons of eight privacy mechanisms. We found that owner registration and automatic face blurring individually received most support from both controllers and bystanders. Our respondents also suggested using varied combinations of mechanisms under different drone usage scenarios, highlighting their context-dependent preferences. We outline a set of important questions for future privacy designs and public policies of drones. Copyright is held by the owner/author(s). Publication rights licensed to ACM.",

keywords = "Drone, Perceptions, Privacy mechanisms, UAS, UAV",

author = "Yaxing Yao and Huichuan Xia and Yun Huang and Yang Wang",

year = "2017",

month = may,

day = "2",

doi = "10.1145/3025453.3025907",

language = "English (US)",

volume = "2017-May",

pages = "6777--6788",

booktitle = "CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems",

publisher = "Association for Computing Machinery",

note = "2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017 ; Conference date: 06-05-2017 Through 11-05-2017",

}

TY - GEN

T1 - Privacy mechanisms for drones

T2 - 2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017

AU - Yao, Yaxing

AU - Xia, Huichuan

AU - Huang, Yun

AU - Wang, Yang

PY - 2017/5/2

Y1 - 2017/5/2

N2 - Drones pose privacy concerns such as surveillance and stalking. Many technology-based or policy-based mechanisms have been proposed to mitigate these concerns. However, it is unclear how drone controllers and bystanders perceive these mechanisms and whether people intend to adopt them. In this paper, we report results from two rounds of online survey with 169 drone controllers and 717 bystanders in the U.S. We identified respondents' perceived pros and cons of eight privacy mechanisms. We found that owner registration and automatic face blurring individually received most support from both controllers and bystanders. Our respondents also suggested using varied combinations of mechanisms under different drone usage scenarios, highlighting their context-dependent preferences. We outline a set of important questions for future privacy designs and public policies of drones. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

AB - Drones pose privacy concerns such as surveillance and stalking. Many technology-based or policy-based mechanisms have been proposed to mitigate these concerns. However, it is unclear how drone controllers and bystanders perceive these mechanisms and whether people intend to adopt them. In this paper, we report results from two rounds of online survey with 169 drone controllers and 717 bystanders in the U.S. We identified respondents' perceived pros and cons of eight privacy mechanisms. We found that owner registration and automatic face blurring individually received most support from both controllers and bystanders. Our respondents also suggested using varied combinations of mechanisms under different drone usage scenarios, highlighting their context-dependent preferences. We outline a set of important questions for future privacy designs and public policies of drones. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

KW - Drone

KW - Perceptions

KW - Privacy mechanisms

KW - UAS

KW - UAV

UR - http://www.scopus.com/inward/record.url?scp=85044848061&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85044848061&partnerID=8YFLogxK

U2 - 10.1145/3025453.3025907

DO - 10.1145/3025453.3025907

M3 - Conference contribution

AN - SCOPUS:85044848061

VL - 2017-May

SP - 6777

EP - 6788

BT - CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

Y2 - 6 May 2017 through 11 May 2017

ER -