Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
139 tokens/sec
GPT-4o
47 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

A Room With an Overview: Towards Meaningful Transparency for the Consumer Internet of Things (2401.10669v1)

Published 19 Jan 2024 in cs.HC and cs.CY

Abstract: As our physical environments become ever-more connected, instrumented and automated, it can be increasingly difficult for users to understand what is happening within them and why. This warrants attention; with the pervasive and physical nature of the IoT comes risks of data misuse, privacy, surveillance, and even physical harm. Such concerns come amid increasing calls for more transparency surrounding technologies (in general), as a means for supporting scrutiny and accountability. This paper explores the practical dimensions to transparency mechanisms within the consumer IoT. That is, we consider how smart homes might be made more meaningfully transparent, so as to support users in gaining greater understanding, oversight, and control. Through a series of three user-centric studies, we (i) survey prospective smart home users to gain a general understanding of what meaningful transparency within smart homes might entail; (ii) identify categories of user-derived requirements and design elements (design features for supporting smart home transparency) that have been created through two co-design workshops; and (iii) validate these through an evaluation with an altogether new set of participants. In all, these categories of requirements and interface design elements provide a foundation for understanding how meaningful transparency might be achieved within smart homes, and introduces several wider considerations for doing so.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (138)
  1. G. Chalhoub, M. J. Kraemer, N. Nthala, and I. Flechais, “It did not give me an option to decline: A longitudinal analysis of the user experience of security and privacy in smart home products,” in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, ser. CHI ’21.   New York, NY, USA: Association for Computing Machinery, 2021.
  2. S. Davidoff, M. K. Lee, C. Yiu, J. Zimmerman, and A. K. Dey, “Principles of smart home control,” in Proceedings of the 8th International Conference on Ubiquitous Computing, ser. UbiComp’06.   Berlin, Heidelberg: Springer-Verlag, 2006, pp. 19––34.
  3. T. Jakobi, C. Ogonowski, N. Castelli, G. Stevens, and V. Wulf, “The catch(es) with smart home: Experiences of a living lab field study,” in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems.   New York, NY, USA: Association for Computing Machinery, May 2017, pp. 1620–1633.
  4. S. Zheng, N. Apthorpe, M. Chetty, and N. Feamster, “User perceptions of smart home IoT privacy,” Proceedings of the ACM on Human-Computer Interaction, vol. 2, no. CSCW, pp. 200:1–200:20, Nov. 2018.
  5. K. Westcott, J. Loucks, D. Littmann, P. Wilson, S. Srivastava, and D. Ciampa, “Build it and they will embrace it: Consumers are preparing for 5G connectivity in the home and on the go,” https://www2.deloitte.com/content/dam/insights/us/articles/6457_Mobile-trends-survey/DI_Build-it-and-they-will-embrace-it.pdf, June 2021, accessed: 2021-11-15.
  6. J. Singh, J. Cobbe, and C. Norval, “Decision provenance: Harnessing data flow for accountable systems,” IEEE Access, vol. 7, pp. 6562–6574, 2019.
  7. T. Jakobi, G. Stevens, N. Castelli, C. Ogonowski, F. Schaub, N. Vindice, D. Randall, P. Tolmie, and V. Wulf, “Evolving needs in IoT control and accountability: A longitudinal study on smart home intelligibility,” Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 2, no. 4, pp. 171:1–171:28, Dec. 2018.
  8. M. Tabassum, T. Kosinski, and H. R. Lipford, “I don’t own the data: End user perceptions of smart home device data practices and risks,” in Fifteenth Symposium on Usable Privacy and Security (SOUPS 2019).   Santa Clara, CA: USENIX Association, Aug. 2019, pp. 435–450.
  9. C. Norval, J. Cobbe, and J. Singh, “Towards an accountable Internet of Things: A call for ‘reviewability’,” in Privacy by Design for the Internet of Things: Building accountability and security.   The Institution of Engineering Technology, 2021.
  10. A. Crabtree, T. Lodge, J. Colley, C. Greenhalgh, K. Glover, H. Haddadi, Y. Amar, R. Mortier, Q. Li, J. Moore et al., “Building accountability into the Internet of Things: the IoT Databox model,” Journal of Reliable Intelligent Environments, vol. 4, no. 1, pp. 39–55, 2018.
  11. A. Carman, “Smart ovens have been turning on overnight and preheating to 400 degrees,” https://www.theverge.com/2019/8/14/20802774/june-smart-oven-remote-preheat-update-user-error, August 2019, accessed: 2021-11-15.
  12. R. Trimananda, S. A. H. Aqajari, J. Chuang, B. Demsky, G. H. Xu, and S. Lu, “Understanding and automatically detecting conflicting interactions between smart home IoT applications,” in Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ser. ESEC/FSE 2020.   New York, NY, USA: Association for Computing Machinery, 2020, pp. 1215––1227.
  13. A. Acquisti, I. Adjerid, and L. Brandimarte, “Gone in 15 seconds: The limits of privacy transparency and control,” IEEE Security & Privacy, vol. 11, no. 4, pp. 72–74, 2013.
  14. M. Bovens, “Analysing and assessing accountability: A conceptual framework1,” European Law Journal, vol. 13, no. 4, pp. 447–468, 2007.
  15. J. A. Obar, “Sunlight alone is not a disinfectant: Consent and the futility of opening big data black boxes (without assistance),” Big Data & Society, vol. 7, no. 1, pp. 1–5, 2020.
  16. C. Stohl, M. Stohl, and P. M. Leonardi, “Managing opacity: Information visibility and the paradox of transparency in the digital age,” IJoC, vol. 10, no. 2016, pp. 123–137, 2016.
  17. N. Suzor, S. West, A. Quodling, and J. York, “What do we mean when we talk about transparency? Toward meaningful transparency in commercial content moderation,” International Journal of Communication, vol. 13, no. 0, 2019.
  18. D. Kamarinou, C. Millard, and J. Singh, “Machine learning with personal data,” in Data protection and privacy: The age of intelligent machines.   Hart Publishing, 2017.
  19. J. Cobbe, M. S. A. Lee, and J. Singh, “Reviewable automated decision-making: A framework for accountable algorithmic systems,” in Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, ser. FAccT ’21.   New York, NY, USA: Association for Computing Machinery, 2021, pp. 598––609.
  20. M. Kaminski and J. M. Urban, “The right to contest AI,” Columbia Law Review, vol. 121, no. 7, 2021.
  21. J. Pridmore and A. Mols, “Personal choices and situated data: Privacy negotiations and the acceptance of household intelligent personal assistants,” Big Data & Society, vol. 7, no. 1, 2020.
  22. J. Ausloos and M. Veale, “Researching with data rights,” Technology and Regulation, vol. 2020, pp. 136–157, Jan. 2021.
  23. K. Holtzblatt and H. R. Beyer, “Requirements gathering: The human factor,” Commun. ACM, vol. 38, no. 5, pp. 31––32, May 1995.
  24. C. Norval, K. Cornelius, J. Cobbe, and J. Singh, “Disclosure by design: Designing information disclosures to support meaningful transparency and accountability,” in 2022 ACM Conference on Fairness, Accountability, and Transparency, ser. FAccT ’22.   New York, NY, USA: Association for Computing Machinery, 2022, pp. 679––690.
  25. D. Miorandi, S. Sicari, F. De Pellegrini, and I. Chlamtac, “Internet of Things: Vision, applications and research challenges,” Ad Hoc Networks, vol. 10, no. 7, pp. 1497–1516, 2012.
  26. J. Singh, T. Pasquier, J. Bacon, H. Ko, and D. Eyers, “Twenty security considerations for Cloud-supported Internet of Things,” IEEE Internet of Things Journal, vol. 3, no. 3, pp. 269–284, 2016.
  27. A. B. Brush, B. Lee, R. Mahajan, S. Agarwal, S. Saroiu, and C. Dixon, “Home automation in the wild: Challenges and opportunities,” in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.   New York, NY, USA: Association for Computing Machinery, May 2011, pp. 2115–2124.
  28. S. Yarosh and P. Zave, “Locked or not? Mental models of IoT feature interaction,” in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, ser. CHI ’17.   New York, NY, USA: Association for Computing Machinery, May 2017, pp. 2993–2997.
  29. D. Roca, D. Nemirovsky, M. Nemirovsky, R. Milito, and M. Valero, “Emergent behaviors in the Internet of Things: The ultimate ultra-large-scale system,” IEEE Micro, vol. 36, no. 6, pp. 36–44, 2016.
  30. W. He, J. Martinez, R. Padhi, L. Zhang, and B. Ur, “When smart devices are stupid: Negative experiences using home smart devices,” in 2019 IEEE Security and Privacy Workshops (SPW), 2019, pp. 150–155.
  31. M. Palekar, E. Fernandes, and F. Roesner, “Analysis of the susceptibility of smart home programming interfaces to end user error,” in 2019 IEEE Security and Privacy Workshops (SPW), 2019, pp. 138–143.
  32. L. Xing, “Cascading failures in Internet of Things: Review and perspectives on reliability and resilience,” IEEE Internet of Things Journal, vol. 8, no. 1, pp. 44–64, 2021.
  33. C. Norval and J. Singh, “Explaining automated environments: Interrogating scripts, logs, and provenance using voice-assistants,” in Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, ser. UbiComp/ISWC ’19 Adjunct, 2019, pp. 332––335.
  34. E. Park, Y. Cho, J. Han, and S. J. Kwon, “Comprehensive approaches to user acceptance of Internet of Things in a smart home environment,” IEEE Internet of Things Journal, vol. 4, no. 6, pp. 2342–2350, 2017.
  35. E.-M. Schomakers, H. Biermann, and M. Ziefle, “Users’ preferences for smart home automation –- Investigating aspects of privacy and trust,” Telematics and Informatics, vol. 64, 2021.
  36. M. Yurrita, T. Draws, A. Balayn, D. Murray-Rust, N. Tintarev, and A. Bozzon, “Disentangling fairness perceptions in algorithmic decision-making: The effects of explanations, human oversight, and contestability,” in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, ser. CHI ’23.   New York, NY, USA: Association for Computing Machinery, 2023.
  37. D. Marikyan, S. Papagiannidis, and E. Alamanos, “A systematic review of the smart home literature: A user perspective,” Technological Forecasting and Social Change, vol. 138, pp. 139–154, 2019.
  38. D. Mocrii, Y. Chen, and P. Musilek, “IoT-based smart homes: A review of system architecture, software, communications, privacy and security,” Internet of Things, vol. 1-2, pp. 81–98, 2018.
  39. R. Despouys, R. Sharrock, and I. Demeure, “Sensemaking in the autonomic smart-home,” in Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication.   Seattle Washington: ACM, Sep. 2014, pp. 887–894.
  40. Y. Chuang, L.-L. Chen, and Y. Liu, “Design vocabulary for human–IoT systems communication,” in Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems.   New York, NY, USA: Association for Computing Machinery, Apr. 2018, pp. 1–11.
  41. J. Dai, C. Zhang, D. Aliakseyeu, S. Peeters, and W. A. Ijsselsteijn, “The effect of explanation design on user perception of smart home lighting systems: A mixed-method investigation,” in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, ser. CHI ’23.   New York, NY, USA: Association for Computing Machinery, 2023.
  42. İ. Kök, F. Y. Okay, Ö. Muyanlı, and S. Özdemir, “Explainable artificial intelligence (XAI) for Internet of Things: A survey,” IEEE Internet of Things Journal, vol. 10, no. 16, pp. 14 764–14 779, 2023.
  43. A. Desjardins, H. R. Biggs, C. Key, and J. E. Viny, “IoT data in the home: Observing entanglements and drawing new encounters,” in Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems.   New York, NY, USA: Association for Computing Machinery, Apr. 2020, pp. 1–13.
  44. A. Desjardins and H. R. Biggs, “Data epics: Embarking on literary journeys of home Internet of Things data,” in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, ser. CHI ’21.   New York, NY, USA: Association for Computing Machinery, 2021.
  45. N. Castelli, C. Ogonowski, T. Jakobi, M. Stein, G. Stevens, and V. Wulf, “What happened in my home? An end-user development approach for smart home data visualization,” in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems.   New York, NY, USA: Association for Computing Machinery, May 2017, pp. 853–866.
  46. A. Railean and D. Reinhardt, “Let there be LITE: Design and evaluation of a label for IoT transparency enhancement,” in Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, ser. MobileHCI ’18.   New York, NY, USA: Association for Computing Machinery, Sep. 2018, pp. 103–110.
  47. A. Railean and D. Reinhardt, “OnLITE: On-line label for IoT transparency enhancement,” in Secure IT Systems, ser. Lecture Notes in Computer Science.   Springer International Publishing, 2021, pp. 229–245.
  48. M. Manca, F. Paternò, C. Santoro, and L. Corcella, “Supporting end-user debugging of trigger-action rules for IoT applications,” International Journal of Human-Computer Studies, vol. 123, pp. 56–69, 2019.
  49. V. Zhao, L. Zhang, B. Wang, S. Lu, and B. Ur, “Visualizing differences to improve end-user understanding of trigger-action programs,” in Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, ser. CHI EA ’20.   New York, NY, USA: Association for Computing Machinery, 2020, pp. 1––10.
  50. C. Castelluccia, M. Cunche, D. Le Metayer, and V. Morel, “Enhancing transparency and consent in the IoT,” in 2018 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), Apr. 2018, pp. 116–119.
  51. C. Abras, D. Maloney-Krichmar, J. Preece et al., “User-centered design,” Bainbridge, W. Encyclopedia of Human-Computer Interaction. Thousand Oaks: Sage Publications, vol. 37, no. 4, pp. 445–456, 2004.
  52. Y. Yao, L. Huang, Y. He, Z. Ma, X. Xu, and H. Mi, “Reviewing and reflecting on smart home research from the human-centered perspective,” in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, ser. CHI ’23.   New York, NY, USA: Association for Computing Machinery, 2023.
  53. P. Emami-Naeini, H. Dixon, Y. Agarwal, and L. F. Cranor, “Exploring how privacy and security factor into IoT device purchase behavior,” in Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems.   New York, NY, USA: Association for Computing Machinery, May 2019, pp. 1–12.
  54. J. M. Haney, S. M. Furman, and Y. Acar, “Smart home security and privacy mitigations: Consumer perceptions, practices, and challenges,” in HCI for Cybersecurity, Privacy and Trust, ser. Lecture Notes in Computer Science, A. Moallem, Ed.   Cham: Springer International Publishing, 2020, pp. 393–411.
  55. J. Haney, Y. Acar, and S. Furman, “It’s the company, the government, you and I: User perceptions of responsibility for smart home privacy and security,” in 30th USENIX Security Symposium (USENIX Security 21).   USENIX Association, Aug. 2021, pp. 411–428.
  56. O. Kulyk, K. Milanovic, and J. Pitt, “Does my smart device provider care about my privacy? Investigating trust factors and user attitudes in IoT systems,” in Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society, ser. NordiCHI ’20.   New York, NY, USA: Association for Computing Machinery, Oct. 2020, pp. 1–12.
  57. K. Marky, S. Prange, F. Krell, M. Mühlhäuser, and F. Alt, “You just can’t know about everything: Privacy perceptions of smart home visitors,” in 19th International Conference on Mobile and Ubiquitous Multimedia, ser. MUM 2020.   New York, NY, USA: Association for Computing Machinery, 2020, pp. 83––95.
  58. M. Williams, J. R. C. Nurse, and S. Creese, “Privacy is the boring bit: User perceptions and behaviour in the Internet-of-Things,” in 2017 15th Annual Conference on Privacy, Security and Trust (PST), 2017, pp. 181–18 109.
  59. M. Windl, V. Winterhalter, A. Schmidt, and S. Mayer, “Understanding and mitigating technology-facilitated privacy violations in the physical world,” in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, ser. CHI ’23.   New York, NY, USA: Association for Computing Machinery, 2023.
  60. N. Abdi, K. M. Ramokapane, and J. M. Such, “More than smart speakers: Security and privacy perceptions of smart home personal assistants,” in Fifteenth Symposium on Usable Privacy and Security (SOUPS 2019).   Santa Clara, CA: USENIX Association, Aug. 2019, pp. 451–466.
  61. E. Zeng, S. Mare, and F. Roesner, “End user security and privacy concerns with smart homes,” in Thirteenth Symposium on Usable Privacy and Security (SOUPS 2017).   Santa Clara, CA: USENIX Association, Jul. 2017, pp. 65–80.
  62. A. I. Hudig, C. Norval, and J. Singh, “Transparency in the consumer Internet of Things: Data flows and data rights,” http://iot-transparency.org/, 2023, accessed: 2023-08-09.
  63. A. M. Mandalari, D. J. Dubois, R. Kolcun, M. T. Paracha, H. Haddadi, and D. Choffnes, “Blocking without breaking: Identification and mitigation of non-essential IoT traffic,” in Privacy Enhancing Technologies Symposium (PETS), 2021.
  64. J. Ren, D. J. Dubois, D. Choffnes, A. M. Mandalari, R. Kolcun, and H. Haddadi, “Information exposure from consumer IoT devices: A multidimensional, network-informed measurement approach,” in Proceedings of the Internet Measurement Conference, ser. IMC ’19.   New York, NY, USA: Association for Computing Machinery, 2019, pp. 267––279.
  65. N. Apthorpe, Y. Shvartzshnaider, A. Mathur, D. Reisman, and N. Feamster, “Discovering smart home Internet of Things privacy norms using contextual integrity,” Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., vol. 2, no. 2, jul 2018.
  66. Y. Liao, J. Vitak, P. Kumar, M. Zimmer, and K. Kritikos, “Understanding the role of privacy and trust in intelligent personal assistant adoption,” in Information in Contemporary Society, ser. Lecture Notes in Computer Science, N. G. Taylor, C. Christian-Lamb, M. H. Martin, and B. Nardi, Eds.   Cham: Springer International Publishing, 2019, pp. 102–113.
  67. E. Lafontaine, A. Sabir, and A. Das, “Understanding people’s attitude and concerns towards adopting IoT devices,” in Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, no. 307.   New York, NY, USA: Association for Computing Machinery, 2021, pp. 1–10.
  68. S.-C. Cha, T.-Y. Hsu, Y. Xiang, and K.-H. Yeh, “Privacy enhancing technologies in the Internet of Things: Perspectives and challenges,” IEEE Internet of Things Journal, vol. 6, no. 2, pp. 2159–2187, 2019.
  69. C. Li and B. Palanisamy, “Privacy in Internet of Things: From principles to technologies,” IEEE Internet of Things Journal, vol. 6, no. 1, pp. 488–505, 2019.
  70. N. Abdi, X. Zhan, K. M. Ramokapane, and J. Such, “Privacy norms for smart home personal assistants,” in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, no. 558.   New York, NY, USA: Association for Computing Machinery, May 2021, pp. 1–14.
  71. Y. Yao, J. R. Basdeo, S. Kaushik, and Y. Wang, “Defending my castle: A co-design study of privacy mechanisms for smart homes,” in Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, ser. CHI ’19.   New York, NY, USA: Association for Computing Machinery, May 2019, pp. 1–12.
  72. Y. Yao, “Designing for better privacy awareness in smart homes,” in Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing, ser. CSCW ’19.   New York, NY, USA: Association for Computing Machinery, 2019, pp. 98––101.
  73. G. Chalhoub, I. Flechais, N. Nthala, R. Abu-Salma, and E. Tom, “Factoring user experience into the security and privacy design of smart home devices: A case study,” in Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, ser. CHI EA ’20.   New York, NY, USA: Association for Computing Machinery, 2020, pp. 1––9.
  74. C. Chhetri and V. G. Motti, “Eliciting privacy concerns for smart home devices from a user centered perspective,” in Information in Contemporary Society, ser. Lecture Notes in Computer Science, N. G. Taylor, C. Christian-Lamb, M. H. Martin, and B. Nardi, Eds.   Cham: Springer International Publishing, 2019, pp. 91–101.
  75. E. Zeng and F. Roesner, “Understanding and improving security and privacy in multi-user smart homes: A design exploration and in-home user study,” in 28th USENIX Security Symposium (USENIX Security 19).   Santa Clara, CA: USENIX Association, Aug. 2019, pp. 159–176.
  76. H. Jin, B. Guo, R. Roychoudhury, Y. Yao, S. Kumar, Y. Agarwal, and J. I. Hong, “Exploring the needs of users for supporting privacy-protective behaviors in smart homes,” in Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, ser. CHI ’22.   New York, NY, USA: Association for Computing Machinery, Apr. 2022, pp. 1–19.
  77. C. Chhetri and V. Motti, “Designing and evaluating a prototype for data-related privacy controls in a smart home,” in Human Aspects of Information Security and Assurance, ser. IFIP Advances in Information and Communication Technology, N. Clarke and S. Furnell, Eds.   Cham: Springer International Publishing, 2022, pp. 240–250.
  78. W. Seymour, M. J. Kraemer, R. Binns, and M. Van Kleek, “Informing the design of privacy-empowering tools for the connected home,” in Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems.   New York, NY, USA: Association for Computing Machinery, Apr. 2020, pp. 1–14.
  79. K. Marky, V. Zimmermann, A. Stöver, P. Hoffmann, K. Kunze, and M. Mühlhäuser, “All in one! User perceptions on centralized IoT privacy settings,” in Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, ser. CHI EA ’20.   New York, NY, USA: Association for Computing Machinery, 2020, pp. 1––8.
  80. L. Urquhart and J. Chen, “On the principle of accountability: Challenges for smart homes & cybersecurity,” CoRR, vol. abs/2006.11043, 2020.
  81. S. Wachter, “The GDPR and the Internet of Things: A three-step transparency model,” Law, Innovation and Technology, vol. 10, no. 2, pp. 266–294, Jul. 2018.
  82. N. Komninos, E. Philippou, and A. Pitsillides, “Survey in smart grid and smart home security: Issues, challenges and countermeasures,” IEEE Communications Surveys & Tutorials, vol. 16, no. 4, pp. 1933–1954, 2014.
  83. F. Meneghello, M. Calore, D. Zucchetto, M. Polese, and A. Zanella, “IoT: Internet of threats? A survey of practical security vulnerabilities in real IoT devices,” IEEE Internet of Things Journal, vol. 6, no. 5, pp. 8182–8201, 2019.
  84. B. K. Mohanta, D. Jena, S. Ramasubbareddy, M. Daneshmand, and A. H. Gandomi, “Addressing security and privacy issues of IoT using blockchain technology,” IEEE Internet of Things Journal, vol. 8, no. 2, pp. 881–888, 2021.
  85. A. Sabir, E. Lafontaine, and A. Das, “Hey Alexa, who am I talking to?: Analyzing users’ perception and awareness regarding third-party Alexa skills,” in Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, ser. CHI ’22.   New York, NY, USA: Association for Computing Machinery, 2022.
  86. K. Zhao and L. Ge, “A survey on the Internet of Things security,” in 2013 Ninth International Conference on Computational Intelligence and Security, 2013, pp. 663–667.
  87. G. Chalhoub, “The UX of Things: Exploring UX principles to inform security and privacy design in the smart home,” in Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, ser. CHI EA ’20.   New York, NY, USA: Association for Computing Machinery, Apr. 2020, pp. 1–6.
  88. Y. H. Hwang, “IoT security & privacy: Threats and challenges,” in Proceedings of the 1st ACM Workshop on IoT Privacy, Trust, and Security, ser. IoTPTS ’15.   New York, NY, USA: Association for Computing Machinery, 2015, p. 1.
  89. C. Geeng and F. Roesner, “Who’s in control? Interactions in multi-user smart homes,” in Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems.   New York, NY, USA: Association for Computing Machinery, May 2019, pp. 1–13.
  90. R. Duezguen, P. Mayer, B. Berens, C. Beckmann, L. Aldag, M. Mossano, M. Volkamer, and T. Strufe, “How to increase smart home security and privacy risk perception,” in 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Oct. 2021, pp. 997–1004, iSSN: 2324-9013.
  91. T. Pasquier, J. Singh, J. Powles, D. Eyers, M. Seltzer, and J. Bacon, “Data provenance to audit compliance with privacy policy in the Internet of Things,” Personal Ubiquitous Comput., vol. 22, no. 2, pp. 333––344, apr 2018.
  92. X. Han, T. Pasquier, A. Bates, J. Mickens, and M. Seltzer, “UNICORN: Runtime provenance-based detector for advanced persistent threats,” in Network and Distributed System Security Symposium (NDSS’20).   Internet Society, 2020.
  93. J. Wang, S. Hao, R. Wen, B. Zhang, L. Zhang, H. Hu, and R. Lu, “IoT-Praetor: Undesired behaviors detection for IoT devices,” IEEE Internet of Things Journal, vol. 8, no. 2, pp. 927–940, 2021.
  94. T. F. J.-M. Pasquier, J. Singh, D. Eyers, and J. Bacon, “Camflow: Managed data-sharing for Cloud services,” IEEE Transactions on Cloud Computing, vol. 5, no. 3, pp. 472–484, 2017.
  95. J. Singh, C. Millard, C. Reed, J. Cobbe, and J. Crowcroft, “Accountability in the IoT: Systems, law, and ways forward,” Computer, vol. 51, no. 7, pp. 54–65, 2018.
  96. P. Emami-Naeini, Y. Agarwal, L. Faith Cranor, and H. Hibshi, “Ask the experts: What should be on an IoT privacy and security label?” in 2020 IEEE Symposium on Security and Privacy (SP), May 2020, pp. 447–464, iSSN: 2375-1207.
  97. Pew Research Center, “Research in the crowdsourcing age, a case study,” https://www.pewresearch.org/internet/2016/07/11/research-in-the-crowdsourcing-age-a-case-study/, July 2016, accessed: 2022-11-14.
  98. F. M. Shipman and C. C. Marshall, “Ownership, privacy, and control in the wake of cambridge analytica: The relationship between attitudes and awareness,” in CHI ’20, 2020, pp. 1––12.
  99. J. Jager, D. L. Putnick, and M. H. Bornstein, “More than just convenient: The scientific merits of homogeneous convenience samples,” Monographs of the Society for Research in Child Development, vol. 82, no. 2, pp. 13–30, 2017.
  100. G. Chalhoub and I. Flechais, “Alexa, are you spying on me?: Exploring the effect of user experience on the security and privacy of smart speaker users,” in HCI for Cybersecurity, Privacy and Trust, A. Moallem, Ed.   Cham: Springer International Publishing, 2020, pp. 305–325.
  101. D. Winder, “How to stop your smart home spying on you,” https://www.theguardian.com/technology/2020/mar/08/how-to-stop-your-smart-home-spying-on-you-lightbulbs-doorbell-ring-google-assistant-alexa-privacy, March 2020, accessed: 2022-08-14.
  102. R. Yus and P. Pappachan, “Smart devices spy on you – 2 computer scientists explain how the Internet of Things can violate your privacy,” https://theconversation.com/smart-devices-spy-on-you-2-computer-scientists-explain-how-the-internet-of-things-can-violate-your-privacy-174579, March 2022, accessed: 2022-08-14.
  103. C. Norval and J. Singh, “Supplementary data — A room with an overview: Towards meaningful transparency for the consumer internet of things,” https://github.com/cnorval/meaningful_IoT, 2023, accessed: 2023-09-18.
  104. H. S. Alavi, E. F. Churchill, M. Wiberg, D. Lalanne, P. Dalsgaard, A. Fatah gen Schieck, and Y. Rogers, “Introduction to Human-Building Interaction (HBI): Interfacing HCI with architecture and urban design,” ACM Trans. Comput.-Hum. Interact., vol. 26, no. 2, mar 2019.
  105. D. Bastos, F. Giubilo, M. Shackleton, and F. El-Moussa, “GDPR privacy implications for the Internet of Things,” in 4th Annual IoT Security Foundation Conference, vol. 4, 2018, pp. 1–8.
  106. V. Braun and V. Clarke, “Using thematic analysis in psychology,” QRP, vol. 3, no. 2, pp. 77–101, 2006.
  107. M. H. Bornstein, J. Jager, and D. L. Putnick, “Sampling in developmental science: Situations, shortcomings, solutions, and standards,” Developmental Review, vol. 33, no. 4, pp. 357–370, 2013.
  108. P. Sedgwick, “Convenience sampling,” BMJ, vol. 347, 2013.
  109. S. J. Stratton, “Population research: Convenience sampling strategies,” Prehospital and Disaster Medicine, vol. 36, no. 4, pp. 373––374, 2021.
  110. MURAL, “MURAL,” https://www.mural.co/, January 2022, accessed: 2022-01-21.
  111. J. Smith and H. Noble, “Bias in research,” Evidence-Based Nursing, vol. 17, no. 4, pp. 100–101, 2014.
  112. M. A. A. Elsood, H. A. Hefny, and E. S. Nasr, “A goal-based technique for requirements prioritization,” in 2014 9th International Conference on Informatics and Systems, 2014, pp. SW–18–SW–24.
  113. A. Cuthbertson, “Hackers can hijack your house through your light bulb, researchers discover,” https://www.independent.co.uk/tech/philips-hue-smart-light-bulb-hack-cyber-security-a9317456.html, February 2020, accessed: 2022-08-13.
  114. E. Ronen and A. Shamir, “Extended functionality attacks on IoT devices: The case of smart lights,” in 2016 IEEE European Symposium on Security and Privacy (EuroS&P), 2016, pp. 3–12.
  115. E. Ronen, A. Shamir, A.-O. Weingarten, and C. O’Flynn, “IoT goes nuclear: Creating a ZigBee chain reaction,” in 2017 IEEE Symposium on Security and Privacy (SP), 2017, pp. 195–212.
  116. E. McGowan, “Here’s what your Ring doorbell knows about you,” https://blog.avast.com/what-amazon-ring-knows-about-you-avast, May 2021, accessed: 2022-08-14.
  117. K. N. Truong, G. R. Hayes, and G. D. Abowd, “Storyboarding: An empirical determination of best practices and effective guidelines,” in Proceedings of the 6th Conference on Designing Interactive Systems, ser. DIS ’06.   New York, NY, USA: Association for Computing Machinery, 2006, pp. 12––21.
  118. W. D. Perreault, “Controlling order-effect bias,” The Public Opinion Quarterly, vol. 39, no. 4, pp. 544–551, 1975.
  119. J. Brooke, “SUS: A quick and dirty usability scale,” in Usability evaluation in industry.   Taylor and Francis, 1996.
  120. A. Bangor, P. Kortum, and J. Miller, “Determining what individual SUS scores mean: Adding an adjective rating scale,” JUS, vol. 4, no. 3, pp. 114–123, 2009.
  121. F. Loukil, C. Ghedira-Guegan, A. N. Benharkat, K. Boukadi, and Z. Maamar, “Privacy-aware in the IoT applications: A systematic literature review,” in On the Move to Meaningful Internet Systems. OTM 2017 Conferences, H. Panetto, C. Debruyne, W. Gaaloul, M. Papazoglou, A. Paschke, C. A. Ardagna, and R. Meersman, Eds.   Cham: Springer International Publishing, 2017, pp. 552–569.
  122. C. M. Gray, Y. Kou, B. Battles, J. Hoggatt, and A. L. Toombs, “The dark (patterns) side of UX design,” in CHI ’18, 2018.
  123. M. Kowalczyk, J. T. Gunawan, D. Choffnes, D. J. Dubois, W. Hartzog, and C. Wilson, “Understanding dark patterns in home IoT devices,” in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, ser. CHI ’23.   New York, NY, USA: Association for Computing Machinery, 2023.
  124. R. Cloete, C. Norval, and J. Singh, “A call for auditable virtual, augmented and mixed reality,” in Proceedings of the 26th ACM Symposium on Virtual Reality Software and Technology, ser. VRST ’20.   New York, NY, USA: Association for Computing Machinery, 2020.
  125. R. Cloete, C. Norval, and J. Singh, “Auditable augmented/mixed/virtual reality: The practicalities of mobile system transparency,” Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., vol. 5, no. 4, dec 2022.
  126. C. Norval, R. Cloete, and J. Singh, “Navigating the audit landscape: A framework for developing transparent and auditable XR,” in Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, ser. FAccT ’23.   New York, NY, USA: Association for Computing Machinery, 2023, pp. 1418––1431.
  127. S. A. Javadi, C. Norval, R. Cloete, and J. Singh, “Monitoring AI services for misuse,” in Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, ser. AIES ’21.   New York, NY, USA: Association for Computing Machinery, 2021, pp. 597––607.
  128. C. Norval, H. Janssen, J. Cobbe, and J. Singh, “Data protection and tech startups: The need for attention, support, and scrutiny,” Policy & Internet, vol. 13, no. 2, pp. 278–299, 2021.
  129. European Union, “Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the Protection of Natural Persons with Regard to the Processing of Personal Data and on the Free Movement of Such Data, and Repealing Directive 95/46/EC (General Data Protection Regulation),” Official Journal of the European Union, vol. L119, pp. 1–88, May 2016.
  130. A. F. T. Winfield, S. Booth, L. A. Dennis, T. Egawa, H. Hastie, N. Jacobs, R. I. Muttram, J. I. Olszewska, F. Rajabiyazdi, A. Theodorou, M. A. Underwood, R. H. Wortham, and E. Watson, “IEEE P7001: A proposed standard on transparency,” Frontiers in Robotics and AI, vol. 8, 2021.
  131. Electronic Frontier Foundation, “Electronic Frontier Foundation,” https://www.eff.org/, January 2022, accessed: 2022-01-20.
  132. Open Rights Group, “Open Rights Group,” https://www.openrightsgroup.org/, January 2022, accessed: 2022-01-20.
  133. J. Chen and L. Urquhart, “They’re all about pushing the products and shiny things rather than fundamental security: Mapping socio-technical challenges in securing the smart home,” arXiv preprint arXiv:2105.11751, 2021.
  134. European Commission, “Europe’s Internet of Things Policy,” https://digital-strategy.ec.europa.eu/en/policies/internet-things-policy, October 2022, accessed: 2022-12-19.
  135. European Commission, “Cyber Resilience Act,” https://digital-strategy.ec.europa.eu/en/library/cyber-resilience-act, September 2022, accessed: 2022-12-19.
  136. GOV.UK, “New cyber security laws to protect smart devices amid pandemic sales surge,” https://www.gov.uk/government/news/new-cyber-security-laws-to-protect-smart-devices-amid-pandemic-sales-surge, April 2021, accessed: 2021-11-15.
  137. GOV.UK, “Code of practice for consumer IoT security,” https://www.gov.uk/government/publications/code-of-practice-for-consumer-iot-security, October 2018, accessed: 2022-12-19.
  138. Article 29 Working Party, “Guidelines on transparency under Regulation 2016/679,” no. WP260, April 2018.
Citations (3)

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets