ReviewA survey of privacy enhancing technologies for smart cities
Introduction
With rapidly growing urban populations, solving problems regarding efficiency and sustainability of cities are becoming relevant and pressing issues. Worldwide concerns of sustainability require action from the global community, individual countries and even every city. Along with sustainability concerns, there are also issues of overpopulation of city centers creating traffic congestion, increases in noise and pollution along with other real or perceived reductions in quality of life. The urban environment encompasses many domains for applications that can be created on the foundation of advancing technologies, all of which have their own obstacles, challenges and opportunities. It is through the creation of solutions in these application domains that the condition of a city can be improved.
Smart cities are generally considered to be the connection of physical, information and communication technology (ICT), social and business infrastructure to improve the overall intelligence in a city operations where intelligence, in a sense, is the ability to make objectively better decisions [1]. Development of Smart Cities is realized through the utilization of different technology streams, such as the Internet of Things (IoT), Cyber–Physical Systems (CPS) or Wireless Sensor Networks (WSN). These technologies create an ecosystem of data that is available for applications and systems that can be designed to achieve the varying goals of a Smart City. Any number of such applications and systems can be imagined, including smart grid, smart buildings, waste management, environmental sensing, health care and smart lighting [2].
While it is important to identify candidate venues for applying such technology-enriched solutions, it is also paramount to recognize and mitigate any risks created by implementing these solutions [3]. For example, compliance with local regulations regarding data collection and usage is imperative for any Smart City. This paper will encompass three main topics surrounding privacy and Smart Cities. First, we review privacy definitions to abstract this complex topic into a model applicable to Smart Cities. Second, we review technologies that allow for the creation of relevant applications and systems that can create benefits for Smart Cities. Third, a review of privacy enhancing technologies is compiled along with an effort to categorize these technologies relative to our definition of privacy in Smart Cities.
The rest of the paper is organized as follows: The various aspects of privacy are introduced in Section 2 followed by information privacy in Section 3. Section 4 introduces the general principles, driving forces, enabling technologies and application domains of Smart Cities with some examples. A comprehensive review of privacy enhancing technologies is presented in Section 5. Section 6 elaborates on applying privacy technologies to Smart City initiatives, and finally a summary and some future works are presented in Section 7.
Section snippets
General principles
Before investigating privacy implications in Smart Cities, an understanding of privacy is required. While privacy can simply be defined as an individual’s right to not be observed or disturbed [4], this view becomes inadequate with the introduction of new and advancing technologies. There are a number of ways to observe someone beyond the simple physical sense. For example, if information regarding a person is recorded and then later revealed, particular aspects of that person’s existence have
General principles
There are two goals when employing privacy enhancing technologies in Smart Cities. The first goal is to protect the identity of each individual who is represented in the data so that no one may learn that they are part of the set. The second goal is to protect all sensitive attributes for each individual. Protecting sensitive attributes is valuable so that, in the case of re-identification, no further information is leaked. Before discussing privacy preservation, it is necessary to categorize
General principles
There are varying ideas of what constitutes a Smart City. Cesana et al. [26] stated that, by 2050, 70% of the world’s population will be living within 2% of the area on earth, generating 75% of the greenhouse gas emissions. Smart Cities are referred to as the methodology of using ICT to increase efficiencies to reduce the impact of large populations living in relatively small areas. As noted by Zhang et al. [27], the urban population is expected to reach 5 billion people by 2030. Sustaining
Privacy enhancing technologies
There are many technologies for protecting privacy, varying from simply removing identifying information to more involved solutions such as random relay networks. It is important to note two broad categories of techniques used to implement privacy protection: (1) Anonymization techniques and (2) Security techniques.
Anonymization techniques change the state of a data set in a way so that no original contributing individual can be identified as being a contributor. This would typically entail
Applying privacy enhancing technologies to smart cities
Thus far, we have discussed Smart City efforts with their privacy implications and described a set of technologies than help protect privacy. In this section, several initiatives listed in Section 4 will be selected to have their privacy concerns addressed through the application of technologies listed in Section 5. With the use of Appendix A, technologies can be selected per requirements at each Smart City architectural layer for categorical or numerical data in order to protect privacy.
For
Summary and future work
As enabling technologies become more sophisticated and more data is collected for Smart City applications, individual privacy is becoming more and more at risk [90]. A few overarching principles and technologies for privacy protection have been outlined here, but this list is not exhaustive. This paper has provided that the responsibility of privacy protection belongs not just to the designers of the applications, but the administrators and users as well.
Future work should include measuring the
Acknowledgments
We acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC), which invests annually over $1 billion in people, discovery and innovation.
Cette recherche a été financee par le Conseil de recherches en sciences naturelles et en génie du Canada (CRSNG) , qui investit chaque année plus d’un milliard de dollars pour soutenir les gens, la découverte et l’innovation.
References (92)
- et al.
Privacy protection in pervasive systems: State of the art and technical challenges
Pervasive Mob. Comput.
(2015) - et al.
Association rules
- et al.
Using ICTs to create a culture of transparency: E-government and social media as openness and anti-corruption tools for societies
Gov. Inf. Q.
(2010) - et al.
Open government, open data and digital government
Gov. Inf. Q.
(2014) - et al.
Efficient data perturbation for privacy preserving and accurate data stream mining
Pervasive Mob. Comput.
(2018) - et al.
Zero knowledge based client side deduplication for encrypted files of secure cloud storage in Smart Cities
Pervasive Mob. Comput.
(2017) - et al.
Smart City architecture: A technology guide for implementation and design challenges
China Commun.
(2014) - et al.
A survey on Internet of Things: Architecture, enabling technologies, security and privacy, and applications
IEEE Internet Things J.
(2017) - . Oxford Living Dictionaries, Privacy, [Online]. Available: https://en.oxforddictionaries.com/definition/us/privacy....
- et al.
Seven Types of Privacy
(2013)
Towards a methodology for statistical disclosure control
Stat. Tidskrift
A taxonomy of privacy
Univ. Pa. Law Rev.
Information privacy: Measuring individuals’ concerns about organizational practices
MIS Q.
The Complete Book of Data Anonymization: from Planning to Implementation
The Right to Privacy in the Digital Age
The OECD Privacy Framework
The EU in Brief
Regulation (EU) 2016/679 of the European Parliament and of the Council
International data-sharing norms: from the OECD to the general data protection regulation (GDPR)
Hum. Genet.
Finding a needle in a haystack or identifying anonymous census records
J. Off. Stat.
K-anonymity: A model for protecting privacy
Internat. J. Uncertain. Fuzziness Knowledge-Based Systems
Database Anonymization: Privacy Models, Data Utility, and Microaggregation-Based Inter-Model Connections
Security and Privacy for the Internet of Things Communication in the SmartCity
The Theory of Dynamic Programming
Differential privacy in the wild
Proc. VLDB Endow.
Revealing information while preserving privacy
IoT communication technologies for Smart Cities
Security and privacy in Smart City applications: Challenges and solutions
IEEE Commun. Mag.
Smart Cities: The Internet of Things, People and Systems
Smart Cities: Definitions, dimensions, performance, and initiatives
J. Urban Technol.
The 3 Generations Of Smart Cities
Large Cities Under Stress: Challenges and Opportunities
Transforming Our World: the 2030 Agenda for Sustainable Development
City-ranking of European Medium-Sized Cities
Understanding Smart Cities: A tool for smart government or an industrial trick?
Smart city architecture: vision and challenges
Int. J. Adv. Comput. Sci. Appl.
The pursuit of citizens’ privacy: a privacy-aware smart city is possible
IEEE Commun. Mag.
Smart health: A context-aware health paradigm within smart cities
IEEE Commun. Mag.
Moments of Life Initiative Begins with Supporting Every Young Child
Contactless Fare Payment for Public Transport in Singapore
Mobility-on-Demand: Real-time Demand-driven Transport through Apps
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2022, Internet of Things (Netherlands)Citation Excerpt :The more data collected from different sources, the more features it will contain; excessive data storage and transfer may face security challenges and privacy breaches. Also, secondary and repeated use of data collected by users without the permission and consent of data owners and unauthorised access is challenging [138]. The set of solutions extracted from various articles to protect data in the smart city is summarized below.