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Special Issue "The Architectures, Systems, and Applications of Internet of Things for Smart Cities"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (31 December 2017)

Special Issue Editors

Guest Editor
Prof. Dr. Yuh-Shyan Chen

Department of Computer Science and Information Engineering, National Taipei University, No. 151, University Rd., San Shia District, New Taipei City, 23741 Taiwan
Website | E-Mail
Interests: wireless sensor networks; fog computing for sensors; software-defined sensors; sensors with 5G; internet of things
Guest Editor
Prof. Dr. Chih-Yung Chang

Department of Computer Science and Information Engineering, Tamkang University, Taipei 251, Taiwan
Website | E-Mail
Interests: internet of things; home care technologies; wireless sensor networks and big data analytics
Guest Editor
Prof. Dr. Tzung-Shi Chen

Department of Computer Science and Information Engineering, National University of Tainan, Tainan 700, Taiwan
Website | E-Mail
Interests: mobile computing; wireless networks; internet of things
Guest Editor
Prof. Dr. Victor C.M. Leung

Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, Canada
Website | E-Mail
Phone: +1-604-822-6932
Fax: +1-604-822-5949
Interests: cognitive wireless networks; big data mobile systems; mobile cloud computing
Guest Editor
Prof. Dr. Sherali Zeadally

College of Communication and Information, University of Kentucky, 315 Little Library Building, Lexington, KY 40506-0224, USA
Website | E-Mail
Interests: Cybersecurity; Privacy; Internet of Things; Computer networks; Mobile computing; Energy-efficient networking

Special Issue Information

Dear Colleagues,

Smart cities are regarded as systems to promote people’s quality of life by using advanced information and communication technology (ICT) and Internet of Things (IoT) solutions to improve the efficiency of services and meet residents' needs in urban environments. IoT can be used to enhance quality, efficiency, and interactivity of urban services, as well as to reduce resource consumption and cost. Nowadays, telecommunication companies, IoT companies, research institutions, and universities are to deploy IoT systems across all dimensions of urban services such as smart grid, smart buildings, smart utility, healthcare, environmental monitoring, smart transportation, smart industries, etc. IoT plays an important role in developing advanced techniques and implementing intelligent systems for smart cities.

This Special Issue aims to address the architectures, systems, and applications of IoT for smart cities. It solicits the state-of-the-art theoretical, as well as practical works on a broad range of issues important on IoT for smart cities for researches, developers, and practitioners from both academia and industry.

Topics of primary interest include, but are not limited to:

  • Architecture design of IoT for smart cites

  • System design of IoT for smart cites

  • Applications of IoT for smart cites

  • Sensing technologies in IoT for smart cities

  • Embedded systems, computing, and networking technology in IoT for smart cities

  • Artificial intelligence, advanced human to machine interaction, machine to machine technologies in smart cites

  • Citizen-centric IoT for smart cities

  • Data collection, fusion and processing technology, and monitoring system design in smart cities

  • Information and communication techniques of IoT for smart cities

  • Smart grid for smart cities

  • Smart transportation and vehicles for smart cities

  • Intelligent control, signal processing technology in IoT for smart cities

  • Energy management and energy efficiency for IoT in smart cities

  • Information security technology and privacy in IoT for smart cities

  • Reliability, self-organization, self-healing, hybrid communication network in IoT for smart cities

  • Wireless rechargeable sensor networks and wireless energy transfer for smart cities

  • Fog computing for smart cities

  • Big data analysis and cloud computing of IoT for smart cities

  • IoT testbed and experiment experiences in smart cities

Prof. Dr. Yuh-Shyan Chen
Prof. Dr. Chih-Yung Chang
Prof. Dr. Tzung-Shi Chen
Prof. Dr. Victor C.M. Leung
Prof. Dr. Sherali Zeadally
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Architecture of IoT

  • System of IoT

  • Applications of IoT

  • Wireless sensor networks

  • Wireless rechargeable sensor networks

  • Security

Published Papers (12 papers)

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Research

Open AccessArticle Replication Strategy for Spatiotemporal Data Based on Distributed Caching System
Sensors 2018, 18(1), 222; doi:10.3390/s18010222
Received: 7 December 2017 / Revised: 5 January 2018 / Accepted: 11 January 2018 / Published: 14 January 2018
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Abstract
The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a
[...] Read more.
The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay. Full article
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Open AccessArticle Performance Analysis of a Novel Hybrid S-ALOHA/TDMA Protocol for Beta Distributed Massive MTC Access
Sensors 2017, 17(12), 2875; doi:10.3390/s17122875
Received: 2 October 2017 / Revised: 5 December 2017 / Accepted: 5 December 2017 / Published: 15 December 2017
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Abstract
Simultaneous random access of massive machine type communications (MTC) devices are expected to cause congestion in the radio access network. Not only the performance of MTC, but the coexisting human to human (H2H) communications would also degrade dramatically without an appropriate medium access
[...] Read more.
Simultaneous random access of massive machine type communications (MTC) devices are expected to cause congestion in the radio access network. Not only the performance of MTC, but the coexisting human to human (H2H) communications would also degrade dramatically without an appropriate medium access control (MAC) protocol. However, most existing solutions focus on the random access procedure without dealing with the sunsequent data transmission procedure. In this paper, we firstly derive a packet size threshold based on the capacity analysis of slotted ALOHA (S-ALOHA) and time division multiple access (TDMA) protocols. Then a novel hybrid S-ALOHA/TDMA MAC protocol (HSTMAC) is presented for massive MTC access, in which the resources are separated for beta distributed machine to machine (M2M) traffic with small size packets and high priority H2H traffic with large size packets. Considering access class barring (ACB) scheme as an overload control method, the system equilibrium under arbitrary retransmission limit is analyzed rigorously, which can provide insights on quality of service (QoS) guarantee. Finally, a dynamic pre-backoff (DPBO) algorithm is designed for load balance by adaptively scattering the highly synchronized M2M traffic over the transmission interval. Numerical and simulation results validate our analysis and show that the HSTMAC protocol is superior to pure S-ALOHA protocol and pure TDMA protocol. The proposed DPBO algorithm can achieve a higher success probability and resource utilization ratio with a much reduced average delay than that of uniform pre-backoff (UPBO) scheme. Full article
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Open AccessArticle A Game-Theory Based Incentive Framework for an Intelligent Traffic System as Part of a Smart City Initiative
Sensors 2017, 17(12), 2874; doi:10.3390/s17122874
Received: 31 October 2017 / Revised: 30 November 2017 / Accepted: 6 December 2017 / Published: 11 December 2017
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Abstract
Intelligent Transportation Systems (ITSs) can be applied to inform and incentivize travellers to help them make cognizant choices concerning their trip routes and transport modality use for their daily travel whilst achieving more sustainable societal and transport authority goals. However, in practice, it
[...] Read more.
Intelligent Transportation Systems (ITSs) can be applied to inform and incentivize travellers to help them make cognizant choices concerning their trip routes and transport modality use for their daily travel whilst achieving more sustainable societal and transport authority goals. However, in practice, it is challenging for an ITS to enable incentive generation that is context-driven and personalized, whilst supporting multi-dimensional travel goals. This is because an ITS has to address the situation where different travellers have different travel preferences and constraints for route and modality, in the face of dynamically-varying traffic conditions. Furthermore, personalized incentive generation also needs to dynamically achieve different travel goals from multiple travellers, in the face of their conducts being a mix of both competitive and cooperative behaviours. To address this challenge, a Rule-based Incentive Framework (RIF) is proposed in this paper that utilizes both decision tree and evolutionary game theory to process travel information and intelligently generate personalized incentives for travellers. The travel information processed includes travellers’ mobile patterns, travellers’ modality preferences and route traffic volume information. A series of MATLAB simulations of RIF was undertaken to validate RIF to show that it is potentially an effective way to incentivize travellers to change travel routes and modalities as an essential smart city service. Full article
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Open AccessArticle Open IoT Ecosystem for Enhanced Interoperability in Smart Cities—Example of Métropole De Lyon
Sensors 2017, 17(12), 2849; doi:10.3390/s17122849
Received: 30 October 2017 / Revised: 30 November 2017 / Accepted: 5 December 2017 / Published: 8 December 2017
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Abstract
The Internet of Things (IoT) has promised a future where everything gets connected. Unfortunately, building a single global ecosystem of Things that communicate with each other seamlessly is virtually impossible today. The reason is that the IoT is essentially a collection of isolated
[...] Read more.
The Internet of Things (IoT) has promised a future where everything gets connected. Unfortunately, building a single global ecosystem of Things that communicate with each other seamlessly is virtually impossible today. The reason is that the IoT is essentially a collection of isolated “Intranets of Things”, also referred to as “vertical silos”, which cannot easily and efficiently interact with each other. Smart cities are perhaps the most striking examples of this problem since they comprise a wide range of stakeholders and service providers who must work together, including urban planners, financial organisations, public and private service providers, telecommunication providers, industries, citizens, and so forth. Within this context, the contribution of this paper is threefold: (i) discuss business and technological implications as well as challenges of creating successful open innovation ecosystems, (ii) present the technological building blocks underlying an IoT ecosystem developed in the framework of the EU Horizon 2020 programme, (iii) present a smart city pilot (Heat Wave Mitigation in Métropole de Lyon) for which the proposed ecosystem significantly contributes to improving interoperability between a number of system components, and reducing regulatory barriers for joint service co-creation practices. Full article
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Open AccessArticle Dynamic Spectrum Access for Internet of Things Service in Cognitive Radio-Enabled LPWANs
Sensors 2017, 17(12), 2818; doi:10.3390/s17122818
Received: 16 October 2017 / Revised: 16 November 2017 / Accepted: 29 November 2017 / Published: 5 December 2017
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Abstract
In this paper, we focus on a dynamic spectrum access strategy for Internet of Things (IoT) applications in two types of radio systems: cellular networks and cognitive radio-enabled low power wide area networks (CR-LPWANs). The spectrum channel contention between the licensed cellular networks
[...] Read more.
In this paper, we focus on a dynamic spectrum access strategy for Internet of Things (IoT) applications in two types of radio systems: cellular networks and cognitive radio-enabled low power wide area networks (CR-LPWANs). The spectrum channel contention between the licensed cellular networks and the unlicensed CR-LPWANs, which work with them, only takes place within the cellular radio spectrum range. Our aim is to maximize the spectrum capacity for the unlicensed users while ensuring that it never interferes with the licensed network. Therefore, in this paper we propose a dynamic spectrum access strategy for CR-LPWANs operating in both licensed and unlicensed bands. The simulation and the numerical analysis by using a matrix geometric approach for the strategy are presented. Finally, we obtain the blocking probability of the licensed users, the mean dwell time of the unlicensed user, and the total carried traffic and combined service quality for the licensed and unlicensed users. The results show that the proposed strategy can maximize the spectrum capacity for the unlicensed users using IoT applications as well as keep the service quality of the licensed users independent of them. Full article
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Open AccessFeature PaperArticle Energy Management in Smart Cities Based on Internet of Things: Peak Demand Reduction and Energy Savings
Sensors 2017, 17(12), 2812; doi:10.3390/s17122812
Received: 2 October 2017 / Revised: 28 November 2017 / Accepted: 29 November 2017 / Published: 5 December 2017
PDF Full-text (1470 KB) | HTML Full-text | XML Full-text
Abstract
Around the globe, innovation with integrating information and communication technologies (ICT) with physical infrastructure is a top priority for governments in pursuing smart, green living to improve energy efficiency, protect the environment, improve the quality of life, and bolster economy competitiveness. Cities today
[...] Read more.
Around the globe, innovation with integrating information and communication technologies (ICT) with physical infrastructure is a top priority for governments in pursuing smart, green living to improve energy efficiency, protect the environment, improve the quality of life, and bolster economy competitiveness. Cities today faces multifarious challenges, among which energy efficiency of homes and residential dwellings is a key requirement. Achieving it successfully with the help of intelligent sensors and contextual systems would help build smart cities of the future. In a Smart home environment Home Energy Management plays a critical role in finding a suitable and reliable solution to curtail the peak demand and achieve energy conservation. In this paper, a new method named as Home Energy Management as a Service (HEMaaS) is proposed which is based on neural network based Q-learning algorithm. Although several attempts have been made in the past to address similar problems, the models developed do not cater to maximize the user convenience and robustness of the system. In this paper, authors have proposed an advanced Neural Fitted Q-learning method which is self-learning and adaptive. The proposed method provides an agile, flexible and energy efficient decision making system for home energy management. A typical Canadian residential dwelling model has been used in this paper to test the proposed method. Based on analysis, it was found that the proposed method offers a fast and viable solution to reduce the demand and conserve energy during peak period. It also helps reducing the carbon footprint of residential dwellings. Once adopted, city blocks with significant residential dwellings can significantly reduce the total energy consumption by reducing or shifting their energy demand during peak period. This would definitely help local power distribution companies to optimize their resources and keep the tariff low due to curtailment of peak demand. Full article
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Open AccessArticle Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator
Sensors 2017, 17(12), 2727; doi:10.3390/s17122727
Received: 20 October 2017 / Revised: 17 November 2017 / Accepted: 22 November 2017 / Published: 25 November 2017
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Abstract
We analyze the feasibility of providing Wireless Sensor Network-data-based services in an Internet of Things scenario from an economical point of view. The scenario has two competing service providers with their own private sensor networks, a network operator and final users. The scenario
[...] Read more.
We analyze the feasibility of providing Wireless Sensor Network-data-based services in an Internet of Things scenario from an economical point of view. The scenario has two competing service providers with their own private sensor networks, a network operator and final users. The scenario is analyzed as two games using game theory. In the first game, sensors decide to subscribe or not to the network operator to upload the collected sensing-data, based on a utility function related to the mean service time and the price charged by the operator. In the second game, users decide to subscribe or not to the sensor-data-based service of the service providers based on a Logit discrete choice model related to the quality of the data collected and the subscription price. The sinks and users subscription stages are analyzed using population games and discrete choice models, while network operator and service providers pricing stages are analyzed using optimization and Nash equilibrium concepts respectively. The model is shown feasible from an economic point of view for all the actors if there are enough interested final users and opens the possibility of developing more efficient models with different types of services. Full article
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Open AccessArticle A Comprehensive System for Monitoring Urban Accessibility in Smart Cities
Sensors 2017, 17(8), 1834; doi:10.3390/s17081834
Received: 21 June 2017 / Revised: 24 July 2017 / Accepted: 7 August 2017 / Published: 9 August 2017
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Abstract
The present work discusses the possibilities offered by the evolution of Information and Communication Technologies with the aim of designing a system to dynamically obtain knowledge of accessibility issues in urban environments. This system is facilitated by technology to analyse the urban user
[...] Read more.
The present work discusses the possibilities offered by the evolution of Information and Communication Technologies with the aim of designing a system to dynamically obtain knowledge of accessibility issues in urban environments. This system is facilitated by technology to analyse the urban user experience and movement accessibility, which enabling accurate identification of urban barriers and monitoring its effectiveness over time. Therefore, the main purpose of the system is to meet the real needs and requirements of people with movement disabilities. The information obtained can be provided as a support service for decision-making to be used by city government, institutions, researchers, professionals and other individuals of society in general to improve the liveability and quality of the lives of citizens. The proposed system is a means of social awareness that makes the most vulnerable groups of citizens visible by involving them as active participants. To perform and implement the system, the latest communication and positioning technologies for smart sensing have been used, as well as the cloud computing paradigm. Finally, to validate the proposal, a case study has been presented using the university environment as a pre-deployment step in urban environments. Full article
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Open AccessArticle Experimental Characterization of Close-Emitter Interference in an Optical Camera Communication System
Sensors 2017, 17(7), 1561; doi:10.3390/s17071561
Received: 22 June 2017 / Revised: 30 June 2017 / Accepted: 30 June 2017 / Published: 4 July 2017
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Abstract
Due to the massive insertion of embedded cameras in a wide variety of devices and the generalized use of LED lamps, Optical Camera Communication (OCC) has been proposed as a practical solution for future Internet of Things (IoT) and smart cities applications. Influence
[...] Read more.
Due to the massive insertion of embedded cameras in a wide variety of devices and the generalized use of LED lamps, Optical Camera Communication (OCC) has been proposed as a practical solution for future Internet of Things (IoT) and smart cities applications. Influence of mobility, weather conditions, solar radiation interference, and external light sources over Visible Light Communication (VLC) schemes have been addressed in previous works. Some authors have studied the spatial intersymbol interference from close emitters within an OCC system; however, it has not been characterized or measured in function of the different transmitted wavelengths. In this work, this interference has been experimentally characterized and the Normalized Power Signal to Interference Ratio (NPSIR) for easily determining the interference in other implementations, independently of the selected system devices, has been also proposed. A set of experiments in a darkroom, working with RGB multi-LED transmitters and a general purpose camera, were performed in order to obtain the NPSIR values and to validate the deduced equations for 2D pixel representation of real distances. These parameters were used in the simulation of a wireless sensor network scenario in a small office, where the Bit Error Rate (BER) of the communication link was calculated. The experiments show that the interference of other close emitters in terms of the distance and the used wavelength can be easily determined with the NPSIR. Finally, the simulation validates the applicability of the deduced equations for scaling the initial results into real scenarios. Full article
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Open AccessArticle Dynamic Resource Allocation and Access Class Barring Scheme for Delay-Sensitive Devices in Machine to Machine (M2M) Communications
Sensors 2017, 17(6), 1407; doi:10.3390/s17061407
Received: 28 March 2017 / Revised: 8 June 2017 / Accepted: 8 June 2017 / Published: 15 June 2017
PDF Full-text (2624 KB) | HTML Full-text | XML Full-text
Abstract
Supporting simultaneous access of machine-type devices is a critical challenge in machine-to-machine (M2M) communications. In this paper, we propose an optimal scheme to dynamically adjust the Access Class Barring (ACB) factor and the number of random access channel (RACH) resources for clustered machine-to-machine
[...] Read more.
Supporting simultaneous access of machine-type devices is a critical challenge in machine-to-machine (M2M) communications. In this paper, we propose an optimal scheme to dynamically adjust the Access Class Barring (ACB) factor and the number of random access channel (RACH) resources for clustered machine-to-machine (M2M) communications, in which Delay-Sensitive (DS) devices coexist with Delay-Tolerant (DT) ones. In M2M communications, since delay-sensitive devices share random access resources with delay-tolerant devices, reducing the resources consumed by delay-sensitive devices means that there will be more resources available to delay-tolerant ones. Our goal is to optimize the random access scheme, which can not only satisfy the requirements of delay-sensitive devices, but also take the communication quality of delay-tolerant ones into consideration. We discuss this problem from the perspective of delay-sensitive services by adjusting the resource allocation and ACB scheme for these devices dynamically. Simulation results show that our proposed scheme realizes good performance in satisfying the delay-sensitive services as well as increasing the utilization rate of the random access resources allocated to them. Full article
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Open AccessArticle Belief Interval of Dempster-Shafer Theory for Line-of-Sight Identification in Indoor Positioning Applications
Sensors 2017, 17(6), 1242; doi:10.3390/s17061242
Received: 8 March 2017 / Revised: 9 May 2017 / Accepted: 23 May 2017 / Published: 30 May 2017
PDF Full-text (5705 KB) | HTML Full-text | XML Full-text
Abstract
Location data are among the most widely used contextual data in context-aware and ubiquitous computing applications. Numerous systems with distinct deployment costs and levels of positioning accuracy have been developed over the past decade for indoor positioning purposes. The most useful method focuses
[...] Read more.
Location data are among the most widely used contextual data in context-aware and ubiquitous computing applications. Numerous systems with distinct deployment costs and levels of positioning accuracy have been developed over the past decade for indoor positioning purposes. The most useful method focuses on the received signal strength (RSS) and provides a set of signal transmission access points. Furthermore, most positioning systems are based on non-line-of-sight (NLOS) rather than line-of-sight (LOS) conditions, and this cause ranging errors for location predictions. Hence, manually compiling a fingerprint database measuring RSS involves high costs and is thus impractical in online prediction environments. In our proposed method, a comparison method is derived on the basis of belief intervals, as proposed in Dempster-Shafer theory, and the signal features are characterized on the LOS and NLOS conditions for different field experiments. The system performance levels were examined with different features and under different environments through robust testing and by using several widely used machine learning methods. The results showed that the proposed method can not only retain positioning accuracy but also save computation time in location predictions. Full article
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Open AccessArticle Attack Classification Schema for Smart City WSNs
Sensors 2017, 17(4), 771; doi:10.3390/s17040771
Received: 16 January 2017 / Revised: 3 March 2017 / Accepted: 1 April 2017 / Published: 5 April 2017
PDF Full-text (1163 KB) | HTML Full-text | XML Full-text
Abstract
Urban areas around the world are populating their streets with wireless sensor networks (WSNs) in order to feed incipient smart city IT systems with metropolitan data. In the future smart cities, WSN technology will have a massive presence in the streets, and the
[...] Read more.
Urban areas around the world are populating their streets with wireless sensor networks (WSNs) in order to feed incipient smart city IT systems with metropolitan data. In the future smart cities, WSN technology will have a massive presence in the streets, and the operation of municipal services will be based to a great extent on data gathered with this technology. However, from an information security point of view, WSNs can have failures and can be the target of many different types of attacks. Therefore, this raises concerns about the reliability of this technology in a smart city context. Traditionally, security measures in WSNs have been proposed to protect specific protocols in an environment with total control of a single network. This approach is not valid for smart cities, as multiple external providers deploy a plethora of WSNs with different security requirements. Hence, a new security perspective needs to be adopted to protect WSNs in smart cities. Considering security issues related to the deployment of WSNs as a main data source in smart cities, in this article, we propose an intrusion detection framework and an attack classification schema to assist smart city administrators to delimit the most plausible attacks and to point out the components and providers affected by incidents. We demonstrate the use of the classification schema providing a proof of concept based on a simulated selective forwarding attack affecting a parking and a sound WSN. Full article
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