The pursuit of citizens' privacy: a privacy-aware smart city is possible
Open accessAbstract
Cities are growing steadily, and the process of urbanization is a common trend in the world. Although cities are getting bigger, they are not necessarily getting better. With the aim to provide citizens with a better place to live, a new concept of a city was born: the smart city. The real meaning of smart city is not strictly defined, but it has gained much attention, and many cities are taking action in order to be considered 'smart'. These smart cities, founded on the use of information and communication technologies, aim at tackling many local problems, from local economy and transportation to quality of life and e-governance. Although technology helps to solve many of these local problems, their ability to gather unprecedented amounts of information could endanger the privacy of citizens. In this article we identify a number of privacy breaches that can appear within the context of smart cities and their services. We leverage some concepts of previously defined privacy models and define the concept of citizens' privacy as a model with five dimensions: identity privacy, query privacy, location privacy, footprint privacy and owner privacy. By means of several examples of smart city services, we define each privacy dimension and show how existing privacy enhancing technologies could be used to preserve citizens' privacy.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Sensitive information relates to several personal facets and domains, creating inter-related privacy forms: identity, bodily, territorial, locational and movement, communications, and transactions privacy.
“Such sensitive information can relate to a number of a personal facets and domains creating a number of inter-related privacy forms including [35,36]:”
From The ethics of smart cities and urban science (2016) · cites this paper as [35]
Sensitive information can relate to a number of personal facets and domains creating a number of inter-related privacy forms, including identity privacy, bodily privacy, territorial privacy, locational and movement privacy, communications privacy, and transactions privacy.
“Such sensitive information can relate to a number of a personal facets and domains creating a number of inter-related privacy forms, including [94,110]:”
From On the sustainability of smart and smarter cities in the era of big data: an interdisciplinary and transdisciplinary literature review (2019) · cites this paper as [94]
Cites
Dwork, C. (2006) · Lecture notes in computer science · doi:10.1007/11787006_1 · Cited by 5,945 · see citing works
Chor, B., Goldreich, O., Eyal Kushilevitz, Z., & Sudan, M. (2002) · Annual Symposium on Foundations of Computer Science · doi:10.1109/sfcs.1995.492461 · Cited by 1,116 · see citing works
Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms
Gedik, B., & Liu, L. (2007) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2007.1062 · Cited by 842 · see citing works
Statistical Disclosure Control
Hundepool, A., Domingo‐Ferrer, J., Franconi, L., Giessing, S., Nordholt, E. S., Spicer, K., & de Wolf, P. (2012) · Wiley eBooks · doi:10.1002/9781118348239 · Cited by 391 · see citing works
Privacy-preserving data mining: why, how, and when
Vaidya, J. S., & Clifton, C. (2004) · IEEE Security & Privacy · doi:10.1109/msp.2004.108 · Cited by 131 · see citing works
Single-Database Private Information Retrieval from Fully Homomorphic Encryption
Yi, X., Kaosar, M. G., Paulet, R., & Bertino, E. (2012) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2012.90 · Cited by 94 · see citing works
A TTP-free protocol for location privacy in location-based services
Solanas, A., & Martínez-Ballesté, A. (2008) · Computer Communications · doi:10.1016/j.comcom.2008.01.007 · Cited by 90 · see citing works
Self-citationA distributed architecture for scalable private RFID tag identification
Solanas, A., Domingo‐Ferrer, J., Martínez-Ballesté, A., et al. (2007) · Computer Networks · doi:10.1016/j.comnet.2007.01.012 · Cited by 51 · see citing works
Self-citationA Three-Dimensional Conceptual Framework for Database Privacy
Domingo‐Ferrer, J. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-75248-6_14 · Cited by 44 · see citing works
Towards a trustworthy privacy in pervasive video surveillance systems
Martínez-Ballesté, A., Rashwan, H. A., Puig, D., et al. (2012) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2012.6197644 · Cited by 17 · see citing works
Location Privacy Through Users' Collaboration: A Distributed Pseudonymizer
Pérez-Martínez, P. A., Solanas, A., & Martínez-Ballesté, A. (2009) · International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM) · doi:10.1109/ubicomm.2009.60 · Cited by 12 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Security and privacy in smart city applications: Challenges and solutions
Zhang, K., Ni, J., Yang, K., Liang, X., Ren, J., & Shen, X. S. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1600267cm · Cited by 638 · see citing works
The ethics of smart cities and urban science
Kitchin, R. (2016) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2016.0115 · Cited by 491 · see citing works
Information centric services in Smart Cities
Piro, G., Cianci, I., Grieco, L. A., Boggia, G., & Camarda, P. (2014) · Journal of Systems and Software · doi:10.1016/j.jss.2013.10.029 · Cited by 349 · see citing works
Bibri, S. E. (2019) · Journal of Big Data · doi:10.1186/s40537-019-0182-7 · Cited by 278 · see citing works
Understanding Smart City—A Data-Driven Literature Review
Stübinger, J., & Schneider, L. (2020) · Sustainability · doi:10.3390/su12208460 · Cited by 118 · see citing works
Towards a secure service provisioning framework in a Smart city environment
Khan, Z., Pervez, Z., & Abbasi, A. G. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.06.031 · Cited by 87 · see citing works
Smart Insiders: Exploring the Threat from Insiders Using the Internet-of-Things
Nurse, J. R. C., Erola, A., Agrafiotis, I., Goldsmith, M., & Creese, S. (2015) · 2015 International Workshop on Secure Internet of Things (SIoT) · doi:10.1109/siot.2015.10 · Cited by 47 · see citing works
- Authors
- Martinez-Balleste, A., Perez-martinez, P., & Solanas, A.
- Venue
- IEEE Communications Magazine
- Published
- 2013-06
- Volume
- 51
- Issue
- 6
- Pages
- 136-141
- ISSN
- 0163-6804 (ISSN-L)
- OpenAlex
- W2141456801
- Cited by
- 307
- References
- 11
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 24 · 2023: 17 · 2022: 20 · 2021: 38 · 2020: 29 · 2019: 36 · 2018: 47 · 2017: 27 · 2016: 18 · 2015: 16 · 2014: 15 · 2013: 7
- FWCI
- 20.65
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- IEEE Communications Magazine (publishedVersion)
- Rovira & Virgili repository (submittedVersion, cc-by)
- Funders
- Generalitat de Catalunya (2009 SGR 1135)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- smart cities, citizen privacy, privacy violations, privacy models, identity privacy, query privacy, location privacy, privacy-enhancing technologies, urbanization, information and communication technologies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
