Internet of Things Application for Intelligent Cities: Security Risk Assessment Challenges

Internet of Things Application for Intelligent Cities: Security Risk Assessment Challenges

Wissam Abbass, Amine Baina, Mostafa Bellafkih
DOI: 10.4018/978-1-7998-5062-5.ch010
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Abstract

The rapid growth of the world's population is placing a huge strain on the existing infrastructures. As a quest for accommodating this growth, interest is turned to the internet of things (IoT). In fact, the IoT is significantly improving today's quality of life by innovating the provided services and enhancing communication and interaction. Furthermore, it has also empowered real-time decision making by introducing dynamic services for innovative traffic handling, energy-efficient infrastructure saving, and public safety ensuring. However, IoT applications for smart cities is still a major issue as it lacks assuring privacy and security within provided services. In this chapter, the authors pinpoint IoT's security risk assessment challenges and examine its critical influence on smart cities. Additionally, they highlight the key aspects characterizing a smart city which also represent the critical assets requiring security risk assessment. Moreover, they discuss the resulting issues and their related countermeasures.
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Introduction

The Internet of Things (IoT) is the latest paradigm spanning various technological fields, from data discovery and processing to networking, device connectivity, and data analysis (Losavio, et al., 2018). It is used in many applications ranging from home security and factory automation to smart living and health care. The IoT offers many benefits and applications to intelligent cities, also called smart cities, including:

  • Optimizing city’s standard services

  • Improving situational awareness

  • Detection and correction of faults

  • Management of infrastructure

  • Better work practices

  • Monitoring air quality

  • Managing city resources

  • Energy monitoring and saving

  • Waste management

  • Better communication capabilities

  • Preventing traffic congestion.

The IoT represents a large set of diverse smart ‘things’ that are equipped with sensors and processing capabilities, connected via the Internet. The number of devices connected to the Internet already exceeds the number of people on earth and is expected to reach 50 to 200 billion devices by 2020 (Bujari and Furini, 2018). Connected devices generate and transmit huge amounts of data that allow citizens to better understand the state and evolution of their cities (Ismagilova, et al., 2019). Additionally, the collected data allows generation of significant insights which later lead to better decision making. Indeed, intelligent transport, smart energy management systems and digital environmental monitoring are all examples of the IoT applications for intelligent cities, also known as digital cities. Furthermore, relying on the IoT tolerates a smart management of the cities’ services. Thus, making tomorrow’s cities smarter and more sustainable by accommodating other devices able to be shared and scalable (Harmon, et al., 2015). Indeed, by conceiving smart cities, citizens are constructively engaged and influence the city management (Cardullo, Paolo, et al., 2019).

As portrayed in Figure 1, an intelligent city designates the incorporation of compound systems within its urban infrastructure allowing smarter living, architecture, mobility, health, environment and government (Ahvenniemi and Huovila, 2017). For instance:

  • The ability to communicate using a smartphone via video in order to allow doctors to check on their patients at home more frequently. Indeed, the patient’s data can be put to use as the benefits can range from an increased use of digital medical monitoring to genomic sequencing to obtain completely personalized treatments.

  • Intelligent waste collection management systems that make it is possible to know the level of waste in real time. Thus, making it possible to optimize the collection routes and reduce the number of kilometers traveled for collection.

  • Better control of energy expenditure where smart cities can also have real-time control of their energy consumption (using smart energy meters) and thus achieve positive savings both for their finances and for the environment.

  • Direct and flexible communication between citizens and their community via technologies such as social media and Web 2.0.

  • An improved public transport network allowing better management of urban traffic and optimizing the real-time flow of infrastructure.

Key Terms in this Chapter

Denial of Service (DoS): An attack shutting down running of a service or network in order to render it inaccessible to its users (whether human person or a processing device).

Malware: Software that is specifically designed to disrupt, damage, or gain unauthorized access to a computer system.

Interoperability: Characteristic of a product or system, whose interfaces are completely understood, to work with other products or systems.

ZigBee: An IEEE 802.15.4-based specification for a suite of high-level communication protocols used to create personal area networks.

Smart or Intelligent Cities: Cities where citizens conserve resources by relying on ICT solutions for maximum efficiency and transparency.

RFID Identifiers: Stands for radio frequency identification – a method for tracking goods by means of tags which transmit a radio signal.

TCP/IP: A set of networking protocols allowing two or more computers to communicate.

Risk Assessment: A systematic process of evaluation and measurement of potential risks that may be involved in a projected activity or undertaking.

Cloud: Remote server and distributed computing environment used to store data and provision computing related services as and when needed on a pay-as-you-go basis.

Urbanization: This refers to the population shift from rural to urban residency, and the technological ways in which each society of people adapts to the technological changes.

Big Data: This refers to extremely large data sets that are analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

Scalability: Property of a system to handle a growing/reducing amount of work by adding or removing resources to the system.

Internet of Things (IoT): This refers to a system of inter-connected computing and smart devices, that are provided with unique identifiers and the ability to transfer data over a network without requiring human interaction.

Sensor: A device that can sense and record physical stimulus (e.g., temperature, speed, pressure, etc.) from physical environments.

Situational Awareness: This is the perception of environmental elements and events with respect to time or space, and the projection of their future status.

Deep Learning: An artificial intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making.

Authentication: The process or action of verifying the identity of a user or process, e.g. verification based on username and password credentials.

Attacker: An entity, a person, or device that attempts to cause harm to an information system or results in a denial of existing service.

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