Abstract
In an Internet of Things (IoT) environment some problems related to user privacy may occur because the exchange of information between devices occurs in a non-standard way. Brazilian data protection law – intended to protect personal data - must also be observed in applications implemented in the Internet of Things environment. This paper presents the IoTPC instrument, which is a tool for measuring privacy in IoT environments and is able to reflect users’ concerns with privacy. IoTPC consists of 17 items that understand users’ opinions on how some IoT devices collect, process, and make their personal information available in some specific IoT scenarios. The IoTPC tool was used in an inference model of the privacy negotiation mechanism for IoT systems. This model makes inferences based on IoTPC items and IoT scenarios using machine learning algorithms that have been trained and tested with IoTPC privacy preferences. The validation of the instrument was made by analyzing the result of a sample of 61 participants, considering the three first order dimensions (IoT requests, decision making and caution) through an exploratory factor analysis. The results of the learning process in the inference model had an accuracy of 79.20%, which indicates that IoTPC can be used in any privacy negotiation mechanism.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aggarwal, C.C.: Data Classification: Algorithms and Applications. CRC Press, London (2014)
Alaba, F.A., Othman, M., Hashem, I.A.T., Alotaibi, F.: Internet of Things security: a survey. J. Netw. Comput. Appl. 88, 10–28 (2017)
Balte, A., Kashid, A., Patil, B.: Security issues in Internet of Things (IOT): a survey. Int. J. Advanced Res. Comput. Sci. Softw. Eng. 5(4), (2015)
Basilevsky, A.T.: Statistical Factor Analysis and Related Methods: Theory and Applications, vol. 418. Wiley, New York (2009)
Buck, C., Burster, S.: App information privacy concerns. In: AMCIS – The Americas Conference on Information Systems (2017)
Field, A.: Discovering Statistics Using IBM SPSS Statistics: North American Edition. SAGE, London (2017)
Guo, K., Tang, Y., Zhang, P.: Csf: crowdsourcing semantic fusion for heterogeneous media big data in the Internet of Things. Inf. Fusion 37, 77–85 (2017)
Koreshoff, T.L., Robertson, T., Leong, T.W.: Internet of Things: a review of literature and products. In: Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration, pp. 335–344. ACM (2013)
Lee, H., Kobsa, A.: Understanding user privacy in Internet of Things environments. In: 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), pp. 407–412. IEEE (2016)
Lu, C.: Overview of security and privacy issues in the Internet of Things. In: Internet of Things (IoT): A vision, Architectural Elements, and Future Directions (2014)
Malhotra, N.K., Kim, S.S., Agarwal, J.: Internet users’ information privacy concerns (IUIPC): the construct, the scale, and a causal model. Inf. Syst. Res. 15(4), 336–355 (2004)
Oriwoh, E., Conrad, M.: “Things” in the Internet of Things: towards a definition. Int. J. Internet Things 4(1), 1–5 (2015)
Peissl, W., Friedewald, M., Burgess, J.P., Bellanova, R., Čas, J.: Introduction: surveillance, privacy and security. In: Surveillance, Privacy and Security, Routledge, pp. 1–12 (2017)
Pereira Couto, F.R., Zorzo, S.: Privacy negotiation mechanism in Internet of Things environments. In: AMCIS – The Americas Conference on Information Systems (2018)
Rokach, L., Maimon, O.: Data Mining with Decision Trees: Theory and Applications. World Scientific, New Jersey (2014)
Smith, H.J., Milberg, S.J., Burke, S.J.: Information privacy: measuring individuals’ concerns about organizational practices. MIS Q. 20, 167–196 (1996)
Streiner, D.L.: Being inconsistent about consistency: when coefficient alpha does and doesn’t matter. J. Pers. Assess. 80(3), 217–222 (2003)
Xu, H., Gupta, S., Rosson, M.B., Carroll, J.M.: Measuring mobile users’ concerns for information privacy. In: Thirty Third International Conference on Information Systems (2012)
Ziegeldorf, J.H., Morchon, O.G., Wehrle, K.: Privacy in the Internet of Things: threats and challenges. Secur. Commun. Netw. 7(12), 2728–2742 (2014)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Lopes, B., de Pontes, D.R.G., Zorzo, S.D. (2019). An Instrument for Measuring Privacy in IoT Environments. In: Latifi, S. (eds) 16th International Conference on Information Technology-New Generations (ITNG 2019). Advances in Intelligent Systems and Computing, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-030-14070-0_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-14070-0_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14069-4
Online ISBN: 978-3-030-14070-0
eBook Packages: EngineeringEngineering (R0)