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The impact of IoT security labelling on consumer product choice and willingness to pay


Autoři: Shane D. Johnson aff001;  John M. Blythe aff001;  Matthew Manning aff002;  Gabriel T. W. Wong aff002
Působiště autorů: Dawes Centre for Future Crime, University College London, London, England, United Kingdom aff001;  ANU Centre for Social Research and Methods, The Australian National University, Canberra, Australia aff002
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0227800

Souhrn

The Internet of Things (IoT) brings internet connectivity to everyday electronic devices (e.g. security cameras and smart TVs) to improve their functionality and efficiency. However, serious security and privacy concerns have been raised about the IoT which impact upon consumer trust and purchasing. Moreover, devices vary considerably in terms of the security they provide, and it is difficult for consumers to differentiate between more and less secure devices. One proposal to address this is for devices to carry a security label to help consumers navigate the market and know which devices to trust, and to encourage manufacturers to improve security. Using a discrete choice experiment, we estimate the potential impact of such labels on participant’s purchase decision making, along with device functionality and price. With the exception of a label that implied weak security, participants were significantly more likely to select a device that carried a label than one that did not. While they were generally willing to pay the most for premium functionality, for two of the labels tested, they were prepared to pay the same for security and functionality. Qualitative responses suggested that participants would use a label to inform purchasing decisions, and that the labels did not generate a false sense of security. Our findings suggest that the use of a security label represents a policy option that could influence behaviour and that should be seriously considered.

Klíčová slova:

Behavior – Communication equipment – Communications – Decision making – Elderly – Internet – Pilot studies – Internet of Things


Zdroje

1. Din I.U., Guizani M., Hassan S., Kim B-S, Khan, Atiquzzaman M., Ahmed S. The Internet of Things: A Review of Enabled Technologies and Future Challenges. IEEE Access. 2018;7:7606–40.

2. Gartner. Gartner Says 6.4 Billion Connected “Things” Will Be in Use in 2016, Up 30 Percent From 2015 [Internet]. 2015. Available from: http://www.gartner.com/newsroom/id/3165317

3. Maple C. Security and privacy in the internet of things. J Cyber Policy. 2017;2(2):155–84.

4. Khan WZ, Aalsalem MY, Khan M., Arshad Q. Enabling Consumer Trust Upon Acceptance of IoT Technologies Through Security and Privacy Model. In: Advanced multimedia and ubiquitous engineering. Springer, Singapore.; 2016. p. 111–7.

5. DCMS. Secure by Design: Improving the cyber security of consumer Internet of Things Report [Internet]. 2018. Available from: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/686089/Secure_by_Design_Report_.pdf

6. Schneier B. Click Here to Kill Everyone [Internet]. 2017. Available from: http://nymag.com/selectall/2017/01/the-internet-of-things-dangerous-future-bruce-schneier.html

7. Lee M; Lee K; Shim J; Cho SJ; Choi J. Security threat on wearable services: Empirical study using a commercial smartband. In: IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia). IEEE; 2016. p. 1–5.

8. Obermaier J, Hutle M. Analyzing the Security and Privacy of Cloud-based Video Surveillance Systems. In: Proceedings of the 2nd ACM International Workshop on IoT Privacy, Trust, and Security—IoTPTS ‘16 [Internet]. New York, New York, USA: ACM Press; 2016. p. 22–8. Available from: http://dl.acm.org/citation.cfm?doid = 2899007.2899008

9. Blythe JM, Johnson SD. A systematic review of cybercrime facilitated by consumer Internet of Things. Secur J. 2019;

10. Cisco. The IoT Value/Trust Paradox [Internet]. 2017. Available from: https://www.jasper.com/resources/reports/iot-value-and-trust-survey?ecid=af_700000005

11. Blythe JM, Sombatruang N, Johnson SD. What security features and crime prevention advice is communicated in consumer IoT device manuals and support pages? J Cyber Secur. 2019;5(1):1–10.

12. DCMS. Government response to the Secure by Design informal consultation [Internet]. 2018. Available from: https://www.gov.uk/government/publications/secure-by-design/government-response-to-the-secure-by-design-informal-consultation

13. Tanczer L, Blythe J, Yahya F, Brass I, Elsden M, Blackstock J, et al. Summary literature review of industry recommendations and international developments on IoT security. 2018.

14. British Standards Institution. BSI launches Kitemark for Internet of Things devices [Internet]. 2018. Available from: https://www.bsigroup.com/en-GB/about-bsi/media-centre/press-releases/2018/may/bsi-launches-kitemark-for-internet-of-things-devices/

15. Talati Z, Norman R, Pettigrew S, Neal B, Kelly B, Dixon H, et al. The impact of interpretive and reductive front-of-pack labels on food choice and willingness to pay. Int J Behav Nutr Phys Act. 2017;14(1):1–10. doi: 10.1186/s12966-016-0456-9

16. Blythe JM, Johnson SD. Rapid evidence assessment on labelling schemes and implications for consumer IoT security. DCMS: London.; 2018.

17. Kalish S, Nelson P. A comparison of ranking, rating and reservation price measurement in conjoint analysis. Mark Lett. 1991;2(4):327–35.

18. Sadler M. Securing our connected world [Internet]. 2017. Available from: https://dcmsblog.uk/2017/10/securing-connected-world/

19. Schneier B. The Internet of Things Is Wildly Insecure—And Often Unpatchable [Internet]. 2014. Available from: https://www.schneier.com/essays/archives/2014/01/the_internet_of_thin.html

20. Nguyen KD, Rosoff H, John RS. Valuing information security from a phishing attack. J Cybersecurity. 2017;3(3):159–71.

21. Rowe B, Wood D. Are Home Internet Users Willing to Pay ISPs for Improvements in Cyber Security? In: In Economics of information security and privacy III. Springer, New York, NY.; 2013. p. 193–212.

22. Bettman JR, Luce MF, Payne JW. Constructive consumer choice processes. J Consum Res. 1988;25(3):187–217.

23. Livingstone S, Haddon L, Görzig A, Ólafsson K. Risks and safety for children on the internet: the UK report [Internet]. Www.Eukidsonline.Net. 2010. Available from: http://www.researchgate.net/publication/50902989_Risks_and_safety_on_the_internet_the_perspective_of_European_children._Full_findings/file/9fcfd5058770fd13fb.pdf

24. Whitty M, Doodson J, Creese S, Hodges D. Individual differences in cyber security behaviors: An examination of who is sharing passwords. Cyberpsychology, Behav Soc Netw [Internet]. 2015;18(1):3–7. Available from: http://search.ebscohost.com/login.aspx?direct=true&db=psyh&AN=2015-01220-002&site=ehost-live%5Cn http://mw229@le.ac.uk

25. Kierkegaard S. Cybering, online grooming and ageplay. Comput Law Secur Rep. 2008;24(1):41–55.

26. Valcke M, Schellens T, Van Keer H, Gerarts M. Primary school children’s safe and unsafe use of the Internet at home and at school: An exploratory study. Comput Human Behav. 2007;23(6):2838–50.

27. Blank G, Bolsover G, Dubois E. A New Privacy Paradox: Young People and Privacy on Social Network Sites. Ssrn. 2014;(April).

28. Sheehan KB. Toward a Typology of Internet Users and Online Privacy Concerns. Inf Soc. 2002;18:21–32.

29. Balleys C, Coll S. Being publicly intimate: teenagers managing online privacy. Media, Cult Soc. 2017;39(6):885–901.

30. Thomas L, Little L, Briggs P, Mcinnes L, Jones E, Nicholson J. Location tracking: Views from the older adult population. Age Ageing. 2013;42(6):758–63. doi: 10.1093/ageing/aft069 23761455

31. Harbach M, De Luca A, Malkin N, Egelman S. Keep on Lockin’ in the Free World: A Multi-National Comparison of Smartphone Locking. Proc 2016 CHI Conf Hum Factors Comput Syst—CHI ‘16 [Internet]. 2016;4823–7. Available from: http://doi.acm.org/10.1145/2858036.2858273

32. Kezer M, Sevi B, Cemalcilar Z, Baruh L. Age differences in privacy attitudes, literacy and privacy management on Facebook. Cyberpsychology. 2016;10(1).

33. Carpenter SM, Yoon C. Aging and consumer decision making. Ann N Y Acad Sci. 2011;1235(1):1–15.

34. Miller LMS, Applegate E, Beckett LA, Wilson MD, Gibson TN. Age differences in the use of serving size information on food labels: Numeracy or attention? Public Health Nutr. 2017;20(5):786–96. doi: 10.1017/S1368980016003219 28025950

35. Talati Z, Pettigrew S, Ball K, Hughes C, Kelly B, Neal B, et al. The relative ability of different front-of-pack labels to assist consumers discriminate between healthy, moderately healthy, and unhealthy foods. Food Qual Prefer [Internet]. 2017;59:109–13. Available from: http://dx.doi.org/10.1016/j.foodqual.2017.02.010

36. FTC. IoT Privacy & Security in a Connected World [Internet]. 2015. Available from: https://www.ftc.gov/system/files/documents/reports/federal-trade-commission-staff-report-november-2013-workshop-entitled-internet-things-privacy/150127iotrpt.pdf

37. Acquisti A, Brandimarte L, Loewenstein G. Privacy and human behavior in the age of information. Science (80-). 2015;347(6221):509–15.

38. Blythe JM, Lefevre CE. Cyberhygiene Insight Report [Internet]. 2017. Available from: https://iotuk.org.uk/wp-content/uploads/2018/01/PETRAS-IoTUK-Cyberhygiene-Insight-Report.pdf

39. Blythe JM, Johnson SD. The Consumer Security Index for IoT: A protocol for developing an index to improve consumer decision making and to incentivize greater security provision in IoT devices. In: Proceedings of the Living in the Internet of Things: Cybersecurity of the IoT Conference. 2018.

40. Sheeran P, Webb TL. The Intention–Behavior Gap. Soc Personal Psychol Compass. 2016;10(9):503–18.

41. Egelman S, Peer E. Scaling the Security Wall: Developing a Security Behavior Intentions Scale (SeBIS). In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems—CHI ‘15 [Internet]. 2015. p. 2873–82. Available from: http://dl.acm.org/citation.cfm?id=2702123.2702249

42. Ryan M, Bate A, Eastmond CJ, Ludbrook A. Use of discrete choice experiments to elicit preferences. Qual Saf Heal Care [Internet]. 2001;10(Supplement 1):i55–60. Available from: http://qualitysafety.bmj.com/lookup/doi/10.1136/qhc.0100055

43. Louviere JJ, Hensher DA, Swait JD. Stated choice methods: analysis and applications. Cambridge university press.; 2000.

44. Kelley P, Bresee J, Cranor L, Reeder R. A nutrition label for privacy. In: Proceedings of the 5th Symposium on Usable Privacy and Security [Internet]. 2009 [cited 2018 Jan 7]. Available from: http://dl.acm.org/citation.cfm?id=1572538

45. Johnson R, Orme B. Getting the most from CBC. Sequim: Sawtooth Software Research Paper Series, Sawtooth Software. 2003.

46. de Bekker-Grob E, Donkers B, Jonker M., Stolk E. Sample size requirements for discrete-choice experiments in healthcare: a practical guide. Patient-Patient-Centered Outcomes Res. 2015;8(5):373–84.

47. Loomis J. 2013 WAEA keynote address: Strategies for overcoming hypothetical bias in stated preference surveys. J Agric Resour Econ. 2014;

48. Egelman S, Peer E. Scaling the Security Wall: Developing a Security Behavior Intentions Scale (SeBIS). Proc 33rd Annu ACM Conf … [Internet]. 2015 [cited 2016 May 27]; Available from: http://dl.acm.org/citation.cfm?id=2702249

49. Cummings R, Taylor LO. American Economic Association Unbiased Value Estimates for Environmental Goods: A Cheap Talk Design for the Contingent Valuation Method Author (s): Ronald G. Cummings and Laura O. Taylor Source: The American Economic Review, Vol. 89, No. 3 (Jun. Am Econ Assoc. 1999;89(3):649–65.

50. Tinelli M. Applying Discrete Choice Experiments in Social Care Research. Methods Rev. 2016;16.

51. McFadden D, Train K. Mixed MNL models for discrete response. J Appl Econom. 2000;15(5):447–70.

52. Train KE. Discrete choice methods with simulation. Cambridge university press; 2009.

53. Hole A. A comparison of approaches to estimating confidence intervals for willingness to pay measures. Health Econ. 2007;16(8):827–40. doi: 10.1002/hec.1197 17238222

54. Loomis J, Kent P, Stange L, Fausch K, Covich A. Measuring the Total Economic Value of Restoring Ecosystem Services in an Impaired River Basin: Results from a Contingent Valuation Survey. Ecol Econ. 2000;33(1):103–17.

55. Alhogail A, Alshahrani M. Building Consumer Trust to Improve Internet of Things (IoT) Technology Adoption. In: International Conference on Applied Human Factors and Ergonomics [Internet]. Springer International Publishing; 2018. p. 325–34. Available from: http://dx.doi.org/10.1007/978-3-319-94866-9_33


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