Karola Marky
Max Mühlhäuser
Florian Alt
ABSTRACT
IoT devices can harvest personal information of any person in their surroundings and this includes data from visitors. Visitors often cannot protect their privacy in a foreign smart environment. This might be rooted in a poor awareness of privacy violations by IoT devices, a lack of knowledge, or a lack of coping strategies. Thus, visitors are typically unaware of being tracked by IoT devices or lack means to influence which data is collected about them. We interviewed 21 young adults to investigate which knowledge visitors of smart environments need and wish to be able and protect their privacy. We found that visitors consider their relation to the IoT device owner and familiarity with the environment and IoT devices when making decisions about data sharing that affect their privacy. Overall, the visitors of smart environments demonstrated similar privacy preferences like the owners of IoT devices but lacked means to judge consequences of data collection and means to express their privacy preferences. Based on our results, we discuss prerequisites for enabling visitor privacy in smart environments, demonstrate gaps in existing solutions and provide several methods to improve the awareness of smart environment visitors.
- Noura Abdi, Kopo M. Ramokapane, and Jose M. Such. 2019. More than Smart Speakers: Security and Privacy Perceptions of Smart Home Personal Assistants. In Proceedings of the Symposium on Usable Privacy and Security(SOUPS ’19). USENIX Association, Berkeley, CA, USA, 1–16.Google Scholar
- Tousif Ahmed, Roberto Hoyle, Patrick Shaffer, Kay Connelly, David Crandall, and Apu Kapadia. 2017. Understanding Physical Safety, Security, and Privacy Concerns of People with Visual Impairments. IEEE Internet Computing 21, 3 (May/June 2017), 56–63. https://doi.org/10.1109/MIC.2017.77Google ScholarDigital Library
- Rawan Alharbi, Mariam Tolba, Lucia C. Petito, Josiah Hester, and Nabil Alshurafa. 2019. To Mask or Not to Mask? Balancing Privacy with Visual Confirmation Utility in Activity-Oriented Wearable Cameras. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3, 3, Article 72 (Sept. 2019), 29 pages. https://doi.org/10.1145/3351230Google ScholarDigital Library
- Florian Alt and Emanuel von Zezschwitz (Eds.). 2019. Special Issue: Emerging Trends in Usable Security and Privacy. Journal of Interactive Media (icom) 18, 3 (Dec. 2019).Google Scholar
- Noah Apthorpe, Yan Shvartzshnaider, Arunesh Mathur, Dillon Reisman, and Nick Feamster. 2018. Discovering Smart Home Internet of Things Privacy Norms Using Contextual Integrity. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 2 (2018), 59. https://doi.org/10.1145/3214262Google ScholarDigital Library
- Ann Blandford, Dominic Furniss, and Stephann Makri. 2016. Qualitative HCI Research: Going Behind the Scenes. Vol. 9. Morgan & Claypool Publishers. 1–115 pages.Google Scholar
- Denys Brand, Florence D. DiGennaro Reed, Mariah D. Morley, Tyler G. Erath, and Matthew D. Novak. 2019. A Survey Assessing Privacy Concerns of Smart-Home Services Provided to Individuals with Disabilities. Behavior Analysis in Practice(2019), 1–11. https://doi.org/10.1007/s40617-018-00329-yGoogle Scholar
- Eun Kyoung Choe, Sunny Consolvo, Jaeyeon Jung, Beverly Harrison, Shwetak N. Patel, and Julie A. Kientz. 2012. Investigating Receptiveness to Sensing and Inference in the Home Using Sensor Proxies. In Proceedings of the Conference on Ubiquitous Computing(UbiComp ’12). ACM, New York, NY, USA, 61–70. https://doi.org/10.1145/2370216.2370226Google ScholarDigital Library
- Soumyadeb Chowdhury, Md Sadek Ferdous, and Joemon M. Jose. 2016. Bystander Privacy in Lifelogging. In Proceedings of the International BCS Human Computer Interaction Conference: Companion Volume (Poole, United Kingdom) (HCI ’16). BCS Learning & Development Ltd., Swindon, UK, Article 15, 3 pages. https://doi.org/10.14236/ewic/HCI2016.62Google ScholarCross Ref
- Hyunji Chung, Michaela Iorga, Jeffrey Voas, and Sangjin Lee. 2017. Alexa, Can I Trust You?Computer 50, 9 (2017), 100–104. https://doi.org/10.1109/MC.2017.3571053Google ScholarDigital Library
- Jessica Colnago, Yuanyuan Feng, Tharangini Palanivel, Sarah Pearman, Megan Ung, Alessandro Acquisti, Lorrie Faith Cranor, and Norman Sadeh. 2020. Informing the Design of a Personalized Privacy Assistant for the Internet of Things. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3313831.3376389Google ScholarDigital Library
- Mary J. Culnan and Pamela K. Armstrong. 1999. Information Privacy Concerns, Procedural Fairness, and Impersonal Trust: An Empirical Investigation. Organization Science 10, 1 (1999), 104–115. https://doi.org/10.1287/orsc.10.1.104Google ScholarDigital Library
- A. Das, M. Degeling, D. Smullen, and N. Sadeh. 2018. Personalized Privacy Assistants for the Internet of Things: Providing Users with Notice and Choice. IEEE Pervasive Computing 17, 3 (Jul 2018), 35–46. https://doi.org/10.1109/MPRV.2018.03367733Google ScholarDigital Library
- Anupam Das, Martin Degeling, Daniel Smullen, and Norman Sadeh. 2018. Personalized Privacy Assistants for the Internet of Things: Providing Users with Notice and Choice. IEEE Pervasive Computing 17, 3 (Jul 2018), 35–46. https://doi.org/10.1109/MPRV.2018.03367733Google ScholarDigital Library
- Jaybie A. de Guzman, Kanchana Thilakarathna, and Aruna Seneviratne. 2018. Security and Privacy Approaches in Mixed Reality: A Literature Survey. Cryptology ePrint Archive, Report 1802.05797. (2018), 1–40. https://doi.org/10.1145/3359626 https://arxiv.org/pdf/1802.05797.pdf.Google ScholarDigital Library
- Tamara Denning, Zakariya Dehlawi, and Tadayoshi Kohno. 2014. In Situ With Bystanders of Augmented Reality Glasses: Perspectives on Recording and Privacy-Mediating Technologies. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems(CHI ’14). ACM, 2377–2386. https://doi.org/10.1145/2556288.2557352Google ScholarDigital Library
- Mariella Dimiccoli, Juan Marín, and Edison Thomaz. 2018. Mitigating Bystander Privacy Concerns in Egocentric Activity Recognition with Deep Learning and Intentional Image Degradation. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 4, Article 132 (Jan. 2018), 18 pages. https://doi.org/10.1145/3161190Google ScholarDigital Library
- Pardis Emami-Naeini, Yuvraj Agarwal, Lorrie Faith Cranor, and Hanan Hibshi. 2020. Ask the Experts: What Should Be on an IoT Privacy and Security Label?arxiv:cs.CY/2002.04631Google Scholar
- Pardis Emami-Naeini, Sruti Bhagavatula, Hana Habib, Martin Degeling, Lujo Bauer, Lorrie Cranor, and Norman Sadeh. 2017. Privacy Expectations and Preferences in an IoT World. In Proceedings of the Symposium on Usable Privacy and Security(SOUPS ’17). USENIX Association, Berkeley, CA, USA, 399–412.Google Scholar
- Pardis Emami-Naeini, Henry Dixon, Yuvraj Agarwal, and Lorrie Faith Cranor. 2019. Exploring How Privacy and Security Factor into IoT Device Purchase Behavior. In Proceedings of the CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). ACM, New York, NY, USA, Article 534, 12 pages. https://doi.org/10.1145/3290605.3300764Google ScholarDigital Library
- Md Sadek Ferdous, Soumyadeb Chowdhury, and Joemon M. Jose. 2017. Analysing privacy in visual lifelogging. Pervasive and Mobile Computing 40 (2017), 430–449. https://doi.org/10.1016/j.pmcj.2017.03.003Google ScholarDigital Library
- Thomas Franke, Christiane Attig, and Daniel Wessel. 2019. A Personal Resource for Technology Interaction: Development and Validation of the Affinity for Technology Interaction (ATI) Scale. International Journal of Human-Computer Interaction 35, 6(2019), 456–467. https://doi.org/10.1080/10447318.2018.1456150 arXiv:https://doi.org/10.1080/10447318.2018.1456150Google ScholarCross Ref
- Christine Geeng and Franziska Roesner. 2019. Who’s In Control?: Interactions In Multi-User Smart Homes. In Proceedings of the CHI Conference on Human Factors in Computing Systems(CHI ’19). ACM, 268. https://doi.org/10.1145/3290605.3300498Google ScholarDigital Library
- Philippe Golle and Kurt Partridge. 2009. On the Anonymity of Home/Work Location Pairs. In Proceedings of the 7th International Conference on Pervasive Computing (Nara, Japan) (Pervasive ’09). Springer-Verlag, Berlin, Heidelberg, 390–397. https://doi.org/10.1007/978-3-642-01516-8_26Google ScholarDigital Library
- Roberto Hoyle, Robert Templeman, Steven Armes, Denise Anthony, David Crandall, and Apu Kapadia. 2014. Privacy Behaviors of Lifeloggers Using Wearable Cameras. In Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (Seattle, Washington) (UbiComp ’14). ACM, New York, NY, USA, 571–582. https://doi.org/10.1145/2632048.2632079Google ScholarDigital Library
- Timo Jakobi, Corinna Ogonowski, Nico Castelli, Gunnar Stevens, and Volker Wulf. 2017. The Catch(Es) with Smart Home: Experiences of a Living Lab Field Study. In Proceedings of the CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI ’17). ACM, New York, NY, USA, 1620–1633. https://doi.org/10.1145/3025453.3025799Google ScholarDigital Library
- Patrick Gage Kelley, Joanna Bresee, Lorrie Faith Cranor, and Robert W Reeder. 2009. A” nutrition label” for privacy. In Proceedings of the 5th Symposium on Usable Privacy and Security. 1–12.Google ScholarDigital Library
- Marion Koelle, Matthias Kranz, and Andreas Möller. 2015. Don’T Look at Me That Way!: Understanding User Attitudes Towards Data Glasses Usage. In Proceedings of the International Conference on Human-Computer Interaction with Mobile Devices and Services (Copenhagen, Denmark) (MobileHCI ’15). ACM, New York, NY, USA, 362–372. https://doi.org/10.1145/2785830.2785842Google ScholarDigital Library
- Marion Koelle, Katrin Wolf, and Susanne Boll. 2018. Beyond LED Status Lights-Design Requirements of Privacy Notices for Body-Worn Cameras. In Proceedings of the International Conference on Tangible, Embedded, and Embodied Interaction(TEI ’18). ACM, New York, NY, USA, 177–187. https://doi.org/10.1145/3173225.3173234Google ScholarDigital Library
- Marc Langheinrich. 2002. A privacy awareness system for ubiquitous computing environments. In international conference on Ubiquitous Computing. Springer, 237–245.Google ScholarCross Ref
- Josephine Lau, Benjamin Zimmerman, and Florian Schaub. 2018. Alexa, Are You Listening?: Privacy Perceptions, Concerns and Privacy-Seeking Behaviors With Smart Speakers. Proceedings of the ACM Conference on Human-Computer Interaction 2, CSCW(2018), 102. https://doi.org/10.1145/3274371Google ScholarDigital Library
- Scott Lederer, Jennifer Mankoff, and Anind K. Dey. 2003. Who Wants to Know What When? Privacy Preference Determinants in Ubiquitous Computing. In CHI ’03 Extended Abstracts on Human Factors in Computing Systems (Ft. Lauderdale, Florida, USA) (CHI EA ’03). Association for Computing Machinery, New York, NY, USA, 724–725. https://doi.org/10.1145/765891.765952Google ScholarDigital Library
- Shrirang Mare, Franziska Roesner, and Tadayoshi Kohno. 2020. Smart Devices in Airbnbs: Considering Privacy and Security for both Guests and Hosts. Proceedings on Privacy Enhancing Technologies 2020, 2(2020), 436–458.Google ScholarCross Ref
- Karola Marky, Alexandra Voit, Alina Stöver, Kai Kunze, Svenja Schröder, and Max Mühläuser. 2020. “I don’t know how to protect myself”: Understanding Privacy Perceptions Resulting from the Presence of Bystanders in Smart Environments. In Proceedings of the NordiCHI Nordic conference on Human-computer Interaction(NordiCHI ’20). ACM, New York, USA.Google ScholarDigital Library
- Terence V. McCann and Eileen Clark. 2003. Grounded Theory in Nursing Research: Part 1 – Methodology. (2003).Google Scholar
- Emily McReynolds, Sarah Hubbard, Timothy Lau, Aditya Saraf, Maya Cakmak, and Franziska Roesner. 2017. Toys That Listen: A Study of Parents, Children, and Internet-Connected Toys. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI ’17). Association for Computing Machinery, New York, NY, USA, 5197–5207. https://doi.org/10.1145/3025453.3025735Google ScholarDigital Library
- Mateusz Mikusz, Steven Houben, Nigel Davies, Klaus Moessner, and Marc Langheinrich. 2018. Raising Awareness of IoT Sensor Deployments. In Proceedings of the Living in the Internet of Things: Cybersecurity of the IoT. IET. https://doi.org/10.1049/cp.2018.0009Google ScholarCross Ref
- Vivian Genaro Motti and Kelly Caine. 2015. Users’ Privacy Concerns About Wearables. In Proceedings of the International Conference on Financial Cryptography and Data Security(FC ’15). Springer, 231–244. https://doi.org/10.1007/978-3-662-48051-9_17Google ScholarCross Ref
- David H. Nguyen, Alfred Kobsa, and Gillian R. Hayes. 2008. An Empirical Investigation of Concerns of Everyday Tracking and Recording Technologies. In Proceedings of the International Conference on Ubiquitous Computing (Seoul, Korea) (UbiComp ’08). Association for Computing Machinery, New York, NY, USA, 182–191. https://doi.org/10.1145/1409635.1409661Google ScholarDigital Library
- Briony J. Oates. 2005. Researching Information Systems and Computing. Sage.Google ScholarDigital Library
- Alfredo Perez, Sherali Zeadally, Luis Matos Garcia, Jaouad Mouloud, and Scott Griffith. 2018. FacePET: Enhancing Bystanders’ Facial Privacy with Smart Wearables/Internet of Things. Electronics 7, 12 (2018), 379. https://doi.org/10.3390/electronics7120379Google ScholarCross Ref
- Sarah Pidcock, Rob Smits, Urs Hengartner, and Ian Goldberg. 2011. Notisense: An Urban Sensing Notification System to Improve Bystander Privacy. In Proceedings of the International Workshop Sensing Applications on Mobile Phones(PhoneSense ’11). 1–5.Google Scholar
- Rebecca S Portnoff, Linda N Lee, Serge Egelman, Pratyush Mishra, Derek Leung, and David Wagner. 2015. Somebody’s watching me? assessing the effectiveness of webcam indicator lights. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. 1649–1658.Google Scholar
- Stefanie Pötzsch. 2008. Privacy awareness: A means to solve the privacy paradox?. In IFIP Summer School on the Future of Identity in the Information Society. Springer, 226–236.Google Scholar
- Olivia K. Richards. 2019. Family-Centered Exploration of the Benefits and Burdens of Digital Home Assistants. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems(CHI EA ’19). ACM, SRC11. https://doi.org/10.1145/3290607.3308458Google ScholarDigital Library
- Tom A. Rodden, Joel E. Fischer, Nadia Pantidi, Khaled Bachour, and Stuart Moran. 2013. At Home with Agents: Exploring Attitudes Towards Future Smart Energy Infrastructures. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI ’13). ACM, New York, NY, USA, 1173–1182. https://doi.org/10.1145/2470654.2466152Google ScholarDigital Library
- Yunpeng Song, Yun Huang, Zhongmin Cai, and Jason I. Hong. 2020. I’m All Eyes and Ears: Exploring Effective Locators for Privacy Awareness in IoT Scenarios. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3313831.3376585Google ScholarDigital Library
- Statista. 2019. Smart Home Worldwirde. https://www.statista.com/outlook/279/100/smart-home/worldwide(Accessed January 2020).Google Scholar
- Madiha Tabassum, Tomasz Kosinski, and Heather Richter Lipford. 2019. I Don’t Own the Data”: End User Perceptions of Smart Home Device Data Practices and Risks. In Proceedings of the Fifteenth Symposium on Usable Privacy and Security(SOUPS ’19).Google Scholar
- Christian Tiefenau, Maximilian Häring, Eva Gerlitz, and Emanuel von Zezschwitz. 2019. Making Privacy Graspable: Can we Nudge Users to use Privacy Enhancing Techniques?arxiv:cs.HC/1911.07701Google Scholar
- Blase Ur, Jaeyeon Jung, and Stuart Schechter. 2014. Intruders Versus Intrusiveness: Teens’ and Parents’ Perspectives on Home-entryway Surveillance. In Proceedings of the International Joint Conference on Pervasive and Ubiquitous Computing (Seattle, Washington) (UbiComp ’14). ACM, New York, NY, USA, 129–139. https://doi.org/10.1145/2632048.2632107Google ScholarDigital Library
- E. J. Williams. 1949. Experimental designs balanced for the estimation of residual effects of treatments. Australian Journal of Chemistry 2, 2 (1949), 149–168.Google ScholarCross Ref
- Katrin Wolf, Karola Marky, and Markus Funk. 2018. We should start thinking about Privacy Implications of Sonic Input in Everyday Augmented Reality!Mensch und Computer 2018-Workshopband(2018). https://doi.org/10.18420/muc2018-ws07-0466Google Scholar
- Peter Worthy, Ben Matthews, and Stephen Viller. 2016. Trust Me: Doubts and Concerns Living With the Internet of Things. In Proceedings of the ACM Conference on Designing Interactive Systems(DIS ’16). ACM, New York, NY, USA, 427–434. https://doi.org/10.1145/2901790.2901890Google ScholarDigital Library
- Yaxing Yao, Justin Reed Basdeo, Smirity Kaushik, and Yang Wang. 2019. Defending My Castle: A Co-Design Study of Privacy Mechanisms for Smart Homes. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems(CHI ’19). ACM, New York, NY, USA. https://doi.org/10.1145/3290605.3300428Google ScholarDigital Library
- Yaxing Yao, Justin Reed Basdeo, Oriana Rosata Mcdonough, and Yang Wang. 2019. Privacy Perceptions and Designs of Bystanders in Smart Homes. Proceedings of the ACM on Human-Computer Interaction 3, CSCW(2019), 1–24.Google ScholarDigital Library
- Eric Zeng, Shrirang Mare, and Franziska Roesner. 2017. End User Security & Privacy Concerns with Smart Homes. In Proceedings of the Symposium on Usable Privacy and Security(SOUPS ’17). USENIX Association, Berkeley, CA, USA, 65–80.Google Scholar
- Eric Zeng and Franziska Roesner. 2019. Understanding and Improving Security and Privacy in Multi-User Smart Homes: A Design Exploration and In-Home User Study. In Proceedings of the USENIX Security Symposium(USENIX Security ’19). USENIX Association, Berkeley, CA, USA, 159–176.Google Scholar
- Yu Zhai, Yan Liu, Minghao Yang, Feiyuan Long, and Johanna Virkki. 2014. A Survey Study of the Usefulness and Concerns About Smart Home Applications From the Human Perspective. Open Journal of Social Sciences 2, 11 (2014), 119. https://doi.org/10.4236/jss.2014.211017Google ScholarCross Ref
- Serena Zheng, Noah Apthorpe, Marshini Chetty, and Nick Feamster. 2018. User Perceptions of Smart Home IoT Privacy. Proceedings of the ACM on Human-Computer Interaction 2, CSCW(2018), 200. https://doi.org/10.1145/3274469Google ScholarDigital Library
- Verena Zimmermann, Paul Gerber, Karola Marky, Leon Böck, and Florian Kirchbuchner. 2019. Assessing Users’ Privacy and Security Concerns of Smart Home Technologies. i-com 18, 3 (2019), 197–216. https://doi.org/10.1515/icom-2019-0015Google Scholar
Recommendations
Privacy Perceptions and Designs of Bystanders in Smart Homes
As the Internet of Things (IoT) devices make their ways into people's homes, traditional dwellings are turning into smart homes. While prior empirical studies have examined people's privacy concerns of smart homes and their desired ways of mitigating ...
”I don’t know how to protect myself”: Understanding Privacy Perceptions Resulting from the Presence of Bystanders in Smart Environments
NordiCHI '20: Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping SocietyIoT devices no longer affect single users only because others like visitors or family members - denoted as bystanders - might be in the device’s vicinity. Thus, data about bystanders can be collected by IoT devices and bystanders can observe what IoT ...
User Perceptions of Smart Home IoT Privacy
Smart home Internet of Things (IoT) devices are rapidly increasing in popularity, with more households including Internet-connected devices that continuously monitor user activities. In this study, we conduct eleven semi-structured interviews with smart ...
Comments