Privacy in the Internet of Things: threats and challenges

Introduction to the Special Issue on Evolving IoT and Cyber-Physical Systems: Advancements, Applications, and Solutions

In recent years, people have witnessed numerous Internet of Things (IoT)-based attacks with the exponential increase in the number of IoT devices. Alongside this, the means to secure IoT-based applications are maturing slower than our budding dependence on them. Moreover, the vulnerabilities in an IoT system are exploited in chains to penetrate deep into the network and yield more adverse aftereffects. To mitigate these issues, this paper gives unique insights for handling the growing vulnerabilities in common IoT devices and proposes a threat architecture for IoT, addressing threats in the context of a three-layer IoT reference architecture. Furthermore, the vulnerabilities exploited at the several IoT attack surfaces and the challenges they exert are explored. Thereafter, the challenges in quantifying the IoT vulnerabilities with the existing framework are also analyzed. The study also covers a case study on the Intelligent Transportation System, covering road transport and traffic control specifically in terms of threats and vulnerabilities. Another case study on secure energy management in the Smart Grid is also presented. This case study covers the applications of Internet of Vulnerable Things (IoVT) in Smart energy Grid solutions, as there will be tremendous use of IoT in future Smart Grids to save energy and improve overall distribution. The analysis shows that the integration of the proposed architecture in existing applications alarms the developers about the embedded threats in the system.

Nowadays, the Internet of Things (IoT) applications will increase rapidly, such as smart cities, smart transportation, smart healthcare, and smart things are all composed of the IoT, which connects a wide range of heterogeneous devices. This review paper provides a comprehensive overview of blockchain architectures designed for IoT networks. The IoT has emerged as a sector with enormous impact, potential, and growth, with billions of devices expected to connect to the Internet in the coming years. The first big challenge we will be faced with this big network is security; it must be taken into account. In contrast to other endpoint devices such as smartphones, laptops, and PCs, most IoT devices are more sensitive to assaults. Because of the various specifications and heterogeneity problems, traditional protection primitives cannot be explicitly applied to IoT technologies. This paper investigates these critical and essential issues regarding IoT threats, security requirements, and challenges with particular emphasis on and relation to IoT layered architecture. Next, the paper addresses various existing IoT security technologies to achieve high security for IoT applications. It also addresses how two methods, Blockchain, and context-aware, can help solve many IoT security issues. Finally, the paper assesses and suggests some recommendations for future research in the field of IoT security.

The Internet of Things (IoT) is a rapidly expanding network of interconnected things that use embedded sensors to gather and share data in real‐time. IoT technologies have given rise to many networking applications in our everyday life such as smart homes, smart cities, smart transport, and so forth. Smart healthcare is one such application that has been revolutionized by the IoT, introducing a new branch of IoT known as the Internet of Medical Things (IoMT). IoMT encompasses an entire ecosystem consisting of smart wearable, implantable sensing equipment's or devices, transmitters that are critical for monitoring the patients remotely and continuing the real‐time and has opened the door to new innovative smart healthcare approaches while improving patient care outcomes. IoMT wearable and embedded sensing devices are commonly utilized in smart healthcare to capture medical data and transmit the medical data in a communication network stored in the cloud. The large volume of data generated and transmitted by these IoMT devices is rising at an exponential rate, resulting in an increase in security and privacy vulnerabilities of healthcare data. To ensure the Confidentiality and integrity of the IoMT devices and the sensitive medical data, there should be proper security and privacy measures such as access control, passwords, multifactor authentication, and encryption of data generated, transmitted, or processed in the IoMT framework. In this paper, we identified the internet of things and its applications in smart healthcare systems. Additionally, the paper focuses on the architecture of IoMT, and several challenges, including the IoMT security and privacy requirements, and attack taxonomy. Furthermore, the paper thoroughly investigates both cryptographic and non‐cryptographic based security and privacy‐enhancing techniques for IoMT or healthcare systems with particular emphasis on advancements in key areas such as Homomorphic Encryption, Differential Privacy, and Federated Learning.

Digital technologies influence the everyday lives of individuals, organizations, and society in a variety of ways. One emerging digital technology that has been the subject of much debate in recent years is the Internet of Things (IoT). In the IoT, originally physical objects are equipped with sensors, actors, computing logic, and communication technology. These technology-equipped physical objects, also referred to as smart things, build the nucleus of the IoT. Beyond their role as nucleus of the IoT, smart things can also form product systems, consisting of closely interacting smart things, as well IoT ecosystems, consisting of interacting product systems. The diversity of application fields of the IoT, e.g., Smart City, Smart Mobility, Smart Health, Smart Home, and Smart Factory, provides organizations with a wide range of opportunities. In particular, the IoT affects two elements crucial to an organization’s survival in competitive markets: products and processes. Due to the high potential of the IoT, this doctoral thesis shows how the IoT influences products and processes separately as well as products and processes within an integrated view simultaneously. By connecting the physical with the digital world, the IoT can broaden the range of a product’s functions, e.g., by enabling new digital service offerings. Thus, new products emerge and established products can be further developed. Based on the potential to address customer needs through innovative products, organizations have to decide which smart thing characteristics should be considered by their products in the future (research article #1 and #2). Extending the results of research article #1, research article #2 proposes two classification schemes for smart things, each involving different levels of detail, i.e., a taxonomy of individual smart things and related smart thing clusters. These classification schemes can support organizations, for example, in the development process of smart products. Beyond their influence on products, digital technologies such as the IoT affect business processes along the entire value chain of an organization. However, organizations are still struggling to digitalize business processes and face high levels of uncertainty when determining which technologies they should adopt in order to improve their business processes. To reduce this uncertainty, research article #3 presents a method that guides organizations step-by-step through the identification and selection of digital technologies best suited for improving their business processes. Crucially, the IoT can also affect products and process simultaneously. Based on their fundamental characteristics, smart things can serve as boundary object between customers and organizations, resulting in innovative forms of customer-company and company-company interactions. These innovative interactions lead to changes in the participants’ processes and value propositions. In response, research article #4 presents a domain-specific modeling language that includes all relevant actors – e.g., customers, organizations, and smart things – for designing IoT scenarios with innovative value propositions from a process-oriented and structural view. Research article #5 is thematically linked to research article #4, providing an economic decision model that helps manufacturing organizations to determine and select an optimal sequence of IoT projects with the aim of incorporating IoT technology into the organization’s products, processes, and infrastructure. In particular, the economic feasibility of IoT scenarios in the manufacturing context which were developed with the domain-specific modeling language (research article #4) can be evaluated using the decision model.

Personal health data can come from diverse sources and formats. The heterogeneity of these data sources and the multiple stakeholders involved requires robust, standards-compliant architectures that can adapt to rapidly changing data streams that may be enriched with new types of data from new data endpoints. This chapter surveys the existing state of the art in collecting and managing personal health data primarily available through the Internet of Medical Things (IoMT) devices. Various open-source solutions for generic personal data management require specific consideration if adopted to handle health data collected through IoMT. More specifically, for health data, there are burgeoning open-source initiatives that focus on novel machine learning techniques for personal health data on the “edge.” There are also various commercial solutions in this space, but they all operate in silos, which may need to change to achieve greater connectivity and interoperability. The chapter surveys existing solutions for personal health data management, discuss their strengths, and provides critical analyses of the aspects lacking in these systems. The chapter will conclude with future directions that would ultimately culminate in better IoMT integrated architectures for personal health data collection, storage, and management in a secure and privacy-preserving manner.KeywordsBlockchainConnectivityData managementData storageDistributed ledger technologyElectronic medical recordsFast healthcare interoperability of resourcesHealth dataInternet of medical thingsInteroperabilityMachine learningPersonal health dataPersonal health trainPrivacyRegulationSecuritySensor networksSocial online linked dataTechnical architecturesUse cases

The Internet of Things (IoT), which enables a wide variety of embedded devices, sensors, and actuators (known as smart things) to interconnect and exchange data, is a promising network scenario for bridging physical devices and virtual objects in the cyber world. Considering the limited capacity of smart things, cloud computing has been introduced to store and process the huge amount of data collected by the IoT. The appropriate integration of cloud computing and the IoT can be regarded as the best of two worlds, simultaneously providing omnipresent sensing services and powerful processing capabilities. Undoubtedly, the cloud-assisted IoT will boost the advancement of innovative applications and services including smart cities, industrial IoT, intelligent transportation, and electronic health systems. Despite the benefits of cloud-aided IoT, it is impossible to overlook the significance of security and privacy in this kind of highly heterogeneous and interconnected system. To deal with security threats to smart devices and sensitive data, hundreds of security solutions have recently been put forward for either the cloud or IoT environments. However, a few important characteristics such as heterogeneity and scalability have not been properly considered in these solutions.

Fog/edge computing has been proposed to be integrated with Internet of Things (IoT) to enable computing services devices deployed at network edge, aiming to improve the user’s experience and resilience of the services in case of failures. With the advantage of distributed architecture and close to end-users, fog/edge computing can provide faster response and greater quality of service for IoT applications. Thus, fog/edge computing-based IoT becomes future infrastructure on IoT development. To develop fog/edge computing-based IoT infrastructure, the architecture, enabling techniques, and issues related to IoT should be investigated first, and then the integration of fog/edge computing and IoT should be explored. To this end, this paper conducts a comprehensive overview of IoT with respect to system architecture, enabling technologies, security and privacy issues, and present the integration of fog/edge computing and IoT, and applications. Particularly, this paper first explores the relationship between cyber-physical systems and IoT, both of which play important roles in realizing an intelligent cyber-physical world. Then, existing architectures, enabling technologies, and security and privacy issues in IoT are presented to enhance the understanding of the state of the art IoT development. To investigate the fog/edge computing-based IoT, this paper also investigate the relationship between IoT and fog/edge computing, and discuss issues in fog/edge computing-based IoT. Finally, several applications, including the smart grid, smart transportation, and smart cities, are presented to demonstrate how fog/edge computing-based IoT to be implemented in real-world applications.

The Internet of Things (IoT) involves embedding electronics, software, sensors, and actuators into physical devices, such as vehicles, buildings, and a wide range of smart devices. Network connectivity allows IoT devices to collect and exchange data. The prevalence of IoT devices has increased rapidly in last five years, driven by cheaper electronics and a desire to monitor and control the physical world. We introduce the concept of IoT flood to describe the increased use of IoT devices. Just like the data deluge, the IoT flood has potential benefits and risks. This paper focuses on the hidden side effects of the increased usage of IoT, such as energy consumption, physical pollution, radiation, and health issues. We indicate that an evaluation system with carefully designed metrics reflecting the impact of IoT flood with input from academic, industry, and government is required. We propose some practical measures that can reduce the IoT flood, such as common platforms and data sharing to reduce the side effects. This paper demonstrates the IoT flood problem and potential solutions by examining the intelligent transport system domain where IoT is being deployed to solve problems related to time efficiency and energy consumption through smart mobility.

This study examines intelligent transportation systems and evaluates the applications of the Internet of Things technology in intelligent transportation systems. Moreover, this study discusses the many challenges and benefits of the functionalization of the Internet of Things (IoT) in intelligent transportation systems. Based on the increasing demands of transportation development, the concept of an intelligent transportation system and Internet of Things technology has received increasing attention both in the academic and transportation industries. The increase in traffic accidents in transportation and the lengthening of travel times have led to the emergence of the need for IoT. Developing a sustainable intelligent transportation system requires seamless integration and interoperability with emerging technologies such as connected IoT and vehicles. IoT in intelligent transportation systems decreases the number of vehicles in traffic and reduces harmful gas emissions. Intelligent transportation systems play a key role in increasing traffic safety, optimizing existing road capacity, and reducing delay times. In addition, it contributes to the country’s economy and the environment by reducing the inefficient use of time and energy. The IoT in intelligent transportation systems will be one of the most important competitive elements for all countries. This study sheds light on IoT technology in intelligent transportation systems and points out possible future research directions.

Privacy preserving Internet of Things: From privacy techniques to a blueprint architecture and efficient implementation

Smart Sensors from Ground to Cloud and Web Intelligence

The Internet of Things (IoT) has been adopted by several areas of society, such as smart transportation systems, smart cities, smart agriculture, smart energy, and smart healthcare. Healthcare is an area that takes a lot of benefits from IoT technology (composing the Internet of Medical Things (IoMT)) since low-cost devices and sensors can be used to create medical assistance systems, reducing the deployment and maintenance costs, and at the same time, improving the patients and their family quality of life. However, only IoT is not able to support the complexity of e-health applications. For instance, sensors can generate a large amount of data, and IoT devices do not have enough computational capabilities to process and store these data. Thus, the cloud and fog technologies emerge to mitigate the IoT limitations, expanding the IoMT applications capacities. Cloud computing provides virtually unlimited computational resources, while fog pushes the resources closest to the end-users, reducing the data transfer latency. Therefore, the IoT, fog, and cloud computing integration provides a robust environment for e-health systems deployment, allowing plenty of different types of IoMT applications. In this paper, we conduct a systematic mapping with the goal to overview the current state-of-the-art in IoMT applications using IoT, fog, and cloud infrastructures.

With the Americans with Disabilities Act (ADA), the past two decades have seen a proliferation of Assistive Technology (AT) and its enabling impact on the lives of people with disabilities in the areas of accessing information, communication, and daily living activities. Due to recent emergence of the Internet of Things (IoT), the research of assistive robotics has been contributing to assisting humans to manipulate and communicate with the robot in complex unstructured environments. The ongoing revolution of Internet of Things (IoT), together with the growing diffusion of robots applied in everyday life and industry, makes Internet of Robotic Things (IoRT) as the future direction for assistive robotics research. New advanced technologies and services are explored in assisting humans. This study provides an overview of the IoT and applications into robotics based on the building blocks of the IoT, along with recent trends and issues relevant to accessing technology for people with disabilities. This research also discusses the technologies in IoT that would benefit the applications of assistive robotics. The most important research challenges to be faced are also highlighted.

Energy management solutions in the Internet of Things applications: Technical analysis and new research directions