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Cited by 38Internet of Things and AIIoT and Edge/Fog ComputingPrivacy, Security, and Data Protection

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

A longitudinal analysis of the public perception of the opportunities and challenges of the Internet of Things

Open access
Zubiaga, Arkaitz, Procter, Rob, Maple, Carsten·2018·PLOS ONE
DOI 10.1371/journal.pone.0209472PMC PMC6301677
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Abstract

The Internet of Things (or IoT), which enables the networked interconnection of everyday objects, is becoming increasingly popular in many aspects of our lives ranging from entertainment to health care. While the IoT brings a set of invaluable advantages and opportunities with it, there is also evidence of numerous challenges that are yet to be resolved. This is certainly the case with regard to ensuring the cyber security of the IoT, and there are various examples of devices being hacked. Despite this evidence, little is known about the public perceptions of the opportunities and challenges presented by the IoT. To advance research in this direction, we mined the social media platform Twitter to learn about public opinion about the IoT. Analysing a longitudinal dataset of more than 6.7 million tweets, we reveal insights into public perceptions of the IoT, identifying big data analytics as the most positive aspect, whereas security issues are the main public concern on the negative side. Our study serves to highlight the importance of keeping IoT devices secure, and remind manufacturers that it is a concern that remains unresolved, at least insofar as the public believes.

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Crossref · 10.1371/journal.pone.0209472

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Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The public views attacks that disseminate sensitive data as seriously as physically destructive attacks.

    “This reinforces recent findings that the public views attacks that disseminate sensitive data as seriously as physically destructive attacks (Zubiaga, Procter, and Maple 2018).”

    From Public Opinion and Cyberterrorism (2023) · cites this paper as Zubiaga, Procter, and Maple 2018

    The Discussion and conclusions (page unavailable) report that IoT security is a major public concern and that posts about it are predominantly negative. The paper does not compare public reactions to attacks that disseminate sensitive data with reactions to physically destructive attacks. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

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Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 33

  1. F Xia, 2012, Internet of things, International Journal of Communication Systems, 25, 1101, 10.1002/dac.2417 · DOI
  2. J Gubbi, 2013, Internet of Things (IoT): A vision, architectural elements, and future directions, Future generation computer systems, 29, 1645, 10.1016/j.future.2013.01.010 · DOI · Paper page
  3. G Reiter, 2014, Wireless connectivity for the Internet of Things, Europe, 433, 868MHz
  4. A Osseiran, 2017, Internet of Things, IEEE Communications Standards Magazine, 1, 84, 10.1109/MCOMSTD.2017.7992936 · DOI
  5. Xu T, Wendt JB, Potkonjak M. Security of IoT systems: Design challenges and opportunities. In: Proceedings of the 2014 IEEE/ACM International Conference on Computer-Aided Design. IEEE Press; 2014. p. 417–423. · DOI
  6. MU Farooq, 2015, A critical analysis on the security concerns of internet of things (IoT), International Journal of Computer Applications, 111, 10.5120/19547-1280 · DOI
  7. Hwang YH. Iot security & privacy: threats and challenges. In: Proceedings of the 1st ACM Workshop on IoT Privacy, Trust, and Security. ACM; 2015. p. 1–1. · DOI
  8. Zhao K, Ge L. A survey on the internet of things security. In: Computational Intelligence and Security (CIS), 2013 9th International Conference on. IEEE; 2013. p. 663–667. · DOI
  9. Tellez M, El-Tawab S, Heydari HM. Improving the security of wireless sensor networks in an IoT environmental monitoring system. In: Systems and Information Engineering Design Symposium (SIEDS), 2016 IEEE. IEEE; 2016. p. 72–77. · DOI
  10. M Stanislav, 2015, Hacking iot: A case study on baby monitor exposures and vulnerabilities, Rapid, 7
  11. D Miessler, 2015, IoT Attack Surface Mapping, DEFCON
  12. SR Islam, 2015, The internet of things for health care: a comprehensive survey, IEEE Access, 3, 678, 10.1109/ACCESS.2015.2437951 · DOI
  13. Q Jing, 2014, Security of the internet of things: Perspectives and challenges, Wireless Networks, 20, 2481, 10.1007/s11276-014-0761-7 · DOI
  14. J Granjal, 2015, Security for the internet of things: a survey of existing protocols and open research issues, IEEE Communications Surveys & Tutorials, 17, 1294, 10.1109/COMST.2015.2388550 · DOI
  15. Sadeghi AR, Wachsmann C, Waidner M. Security and privacy challenges in industrial internet of things. In: Design Automation Conference (DAC), 2015 52nd ACM/EDAC/IEEE. IEEE; 2015. p. 1–6. · DOI
  16. C Maple, 2017, Security and privacy in the internet of things, Journal of Cyber Policy, 2, 155, 10.1080/23738871.2017.1366536 · DOI · Paper page
  17. RH Weber, 2010, Internet of Things–New security and privacy challenges, Computer law & security review, 26, 23, 10.1016/j.clsr.2009.11.008 · DOI
  18. L Atzori, 2010, The internet of things: A survey, Computer networks, 54, 2787, 10.1016/j.comnet.2010.05.010 · DOI · Paper page
  19. M Asplund, 2016, Attitudes and Perceptions of IoT Security in Critical Societal Services, IEEE Access, 4, 2130, 10.1109/ACCESS.2016.2560919 · DOI
  20. N Joseph, 2017, Review of Discussions on Internet of Things (IoT): Insights from Twitter Analytics, Journal of Global Information Management (JGIM), 25, 38, 10.4018/JGIM.2017040103 · DOI
  21. J Bian, 2016, Mining Twitter to Assess the Public Perception of the “Internet of Things”, PloS one, 11, e0158450, 10.1371/journal.pone.0158450 · DOI
  22. A Zubiaga, 2017, Towards real-time, country-level location classification of worldwide tweets, IEEE Transactions on Knowledge and Data Engineering
  23. B Wang, 2017, Proceedings of the European Chapter of the Association for Computational Linguistics, 483
  24. Wang B, Liakata M, Tsakalidis A, Georgakopoulos Kolaitis S, Papadopoulos S, Apostolidis L, et al. TOTEMSS: Topic-based, Temporal Sentiment Summarisation for Twitter. In: Proceedings of the 8th International Joint Conference on Natural Language Processing, IJCNLP; 2017.
  25. DM Blei, 2003, Latent dirichlet allocation, Journal of machine Learning research, 3, 993
  26. Wang B, Liakata M, Zubiaga A, Procter R. A Hierarchical Topic Modelling Approach for Tweet Clustering. In: International Conference on Social Informatics. Springer; 2017. p. 378–390. · DOI
  27. E Ferrara, 2016, The rise of social bots, Communications of the ACM, 59, 96, 10.1145/2818717 · DOI · Paper page
  28. S Castell, 2017, Public Views of Machine Learning, Ipsos MORI
  29. S Castell, 2014, Public attitudes to science 2014, London, Ipsos MORI Social Research Institute, 194, 28
  30. CM Ray, 1999, Men’s and women’s attitudes toward computer technology: A comparison, Office Systems Research Journal, 17, 1
  31. BK Wiederhold, 2014, Marketing analysis of a positive technology app for the self-management of psychological stress, Stud Health Technol Inform, 199, 83
  32. Rao D, Yarowsky D, Shreevats A, Gupta M. Classifying latent user attributes in twitter. In: Proceedings of the workshop on Search and mining user-generated contents; 2010. p. 37–44. · DOI · Paper page
  33. V Venkatesh, 2013, Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems, MIS quarterly, 37, 10.25300/MISQ/2013/37.1.02 · DOI

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Metadata

Authors
Zubiaga, A., Procter, R., & Maple, C.
Affiliations
University of Warwick (GB)
Corresponding author
Zubiaga, Arkaitz
ORCID
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2018-12-20
Volume
13
Issue
12
Pages
e0209472
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0209472
PMC
PMC6301677
OpenAlex
W2902379956
Cited by
38
References
3
Citations by year
2025: 2 · 2024: 3 · 2023: 7 · 2022: 11 · 2021: 6 · 2020: 6 · 2019: 3
FWCI
6.05
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Warwick Research Archive Portal (University of Warwick) (acceptedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Warwick Research Archive Portal (University of Warwick) (submittedVersion)
  • arXiv (Cornell University)
Funders
Engineering and Physical Sciences Research Council (EP/N02334X/1, EP/N510129/1)
Topics
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
Keywords
Internet of Things, public perception, Internet of Things security, cybersecurity, big data analytics, social media sentiment, Twitter, longitudinal analysis, public opinion
MeSH terms
Big Data, Data Analysis, Female, Humans, Longitudinal Studies, Male, Public Opinion, Computer Security, Internet, Social Media, Datasets as Topic

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