IoT Challenges Research Articles

Efficient Lightweight Blockchain with Hybridized Consensus Algorithm for IoT Networks

Blockchain (BC) technology has attracted a lot of interest due to its excellent security and privacy features as well as its immutability. While BC can address security and privacy challenges in IoT, it is often computationally expensive, suffers from limited scalability, and introduces bandwidth overheads and delays, making it unsuitable for IoT applications. This paper proposes a novel lightweight and scalable blockchain (LIGHT-SB) designed specifically for IoT environments. In a smart IoT ecosystem, low-resource devices benefit from a centralized manager that handles communication keys and manages requests. LIGHT-SB enhances decentralization while maintaining robust privacy and security through a hybrid consensus algorithm combining permissionless proof-of-capacity and permissioned Byzantine fault tolerance (PoC-PBFT). Secure message delivery is achieved using SHA-256 and RSA cryptographic techniques. IoT device authentication, communication, and storage are safeguarded within the network. Distributed throughput management is implemented to monitor and adjust BC usage, ensuring it remains efficient. Qualitative evaluations demonstrate that LIGHT-SB effectively mitigates several security threats.

UAV-Assisted IoT Applications, QoS Requirements and Challenges with Future Research Directions

Unmanned Aerial Vehicle (UAV)-assisted Internet of Things application communication is an emerging concept that effectuates the foreknowledge of innovative technologies. With the accelerated advancements in IoT applications, the importance of this technology became more impactful and persistent. Moreover, this technology has demonstrated useful contributions across various domains, ranging from general to specific applications. Examples include wildfire monitoring, coastal area monitoring, deforestation monitoring, and sensitive military operations, where human access is limited or not feasible. These examples underscore the technology’s importance in scenarios where direct human involvement is challenging or impossible. Although this technology offers numerous benefits, it is essential to note that it also faces several challenges. Among these, Quality of Service (QoS) is a key concern, which limits its useability in various applications. Unfortunately, most researchers in the present literature have overlooked this important factor without giving it considerable attention. To fill this gap, we are presenting a systematic review of the present literature associated with the QoS metrics of this emerging technology from 2015 to 2023 to highlight their contributions and limitations. Based on the systematic review, we highlight the open challenges of this technology to set a roadmap for futuristic research. Finally, we compared each portion of this work with the previously published review articles to confirm the essence of this work, along with an explanation of why this survey is needed and in-time.

Teachers’ perceptions about IoT technologies in school activities

ABSTRACT The Internet of Things is shifting the way people interact with each other, the way people interact with objects, and the way objects interact with each other. This reality is creating a new paradigm, where the world becomes more interconnected. In the field of Education, we are at the beginning of understanding the profound transformation that IoT can bring to teaching and learning, namely the exploitation of these technologies as a teaching resource. Despite different approaches, there seems to be a consensus regarding its transformative potential, especially when we think about the concept of hypersituation. This paper presents the main results relating to the teachers’ perception of an IoT-based learning environment supported by a low-cost and open-source IoT device and a set of didactic guides to approach curricular contents of the 7th grade in Portugal. Regarding the organization of the paper, firstly an introductory contextualization is presented, where IoT challenges and potentialities in education are highlighted. After that, we present the followed methodology during the research described. Finally, the results and conclusions, where the perceptions of the involved teachers, regarding the use of IoT technologies in the described contexts are shown and explained.

Integration of data science with the intelligent IoT (IIoT): current challenges and future perspectives

The Intelligent Internet of Things (IIoT) involves real-world things that communicate or interact with each other through networking technologies by collecting data from these “things” and using intelligent approaches, such as Artificial Intelligence (AI) and machine learning, to make accurate decisions. Data science is the science of dealing with data and its relationships through intelligent approaches. Most of the state-of-the-art focus is on the topic independently, either on data science or IIoT. Therefore, to address the gap, this article provides a comprehensive survey on the advances and integration of data science with the Intelligent IoT (IIoT) system by classifying the existing IoT-based data science techniques and presenting a summary of various characteristics. The paper analyzes the data science or big data security and privacy features, including network architecture, data protection, and continuous monitoring of data, which face challenges in various IoT-based systems. Extensive insights into IoT data security, privacy, and challenges are visualized in the context of data science for IoT. In addition, this study reveals the current opportunities to enhance data science and IoT market development. The current gap and challenges faced in the integration of data science and IoT are comprehensively presented, followed by the future outlook and possible solutions to the existing challenges.

Cyber Attack Detection Using Machine Learning Techniques in IoT Networks

The Internet of Things is a rapidly emerging technology (IoT). Thanks to numerous sensors, billions of smart objects (referred to as "Things") may acquire data about themselves and their environment. So they may regulate and monitor industrial services or increase commercial services and activities. However, the Internet of Things is now more vulnerable than ever. Machine Learning (ML) has advanced significantly, bringing up new research avenues to solve current and future IoT challenges. On the other hand, machine learning is an effective method for identifying peril in intelligent devices and networks. Following a thorough literature review on Machine Learning methods and the necessity of IoT security, this study will assess numerous ML algorithms for threat detection and the various security methods, which are associated with Machine Learning techniques.

Convenience, opportunities, risks and challenges of IoT for individual and business consumers: Systematic literature review from 2010 to 2022

IoT offers control over devices and enables users to have real-time monitoring, increased efficiency, and reduced energy costs. As the technology is in its infancy stage, there are several domains that need to be studied. Researchers have made contributions to analyze the key aspects of IoT, including its usage, benefits, risks, and requirement for technological infrastructure. Furthermore, studies were conducted from the consumer’s perspective, aiming to know their preferences and adoption behaviors. This systematic review of literature, based on previous studies from 2010 to 2022, aims to enrich literature while presenting a comprehensive and detailed review of 42 articles from 43 journals and international conferences. The reviewed articles have been selected from databases including Scopus, Web of Science, and Science Direct. The theory development, characteristics, context, and methodology framework (TCCM) has been used to examine these four aspects in consumer behavior regarding IoT devices. The review presents an overview of research in this area and also presents future research directions to spur scholarly research. The research’s contribution to academia and industry is that it provides useful information regarding key aspects of IoT while suggesting new ways for further improvements. The research provides key insights to the IoT industry and how they can overcome product and adoption-related challenges.

INTERNET BASED SUSTAINABLE ENERGY FOR THE ECOSYSTEM

The world has a wealth of renewable and conventional energies, but the lack of technological capabilities and capacities combined with the water-energy requirements limit their benefits to its citizens. Sustainable energy research and innovation will be revolutionized by IoT technologies and the latest IoT communications and sensing approaches. Internet of Things can also be used to address energy challenges for the community by leveraging existing infrastructure such as renewable energy, microgrids and P2G hydrogen systems. This chapter presents the IoT for sustainable energy system approaches, me thods, scenarios and tools, along with a discussion on different sensing techniques and communication technologies. The IoT in Energy Systems is intended to improve the bidirectional exchange of network services by using Internet of Things on grid. This will lead to enhanced system resilience and reliable data flows, as well as connectivity optimization. The sustainable energy IoT challenges and opportunities for innovation are discussed in order to meet the energy needs and economic strength of the energy sector.

A Preliminary Study of Role and Challenges of IOT in Supply Chain Management

Abstract: This paper delves into research on the Internet of Things (IoT) within the context of supply chain management (SCM). It comprehensively addresses the definition of IoT, key technology enablers, various SCM processes, and applications. The Internet of Things has the potential to address limitations in certain aspects of SCM, such as monitoring, production management, logistics operations efficiency, information exchange and communication, supply chain modeling, intelligent information collection, and security. The advent of IoT technology has ushered in a new era in logistics. The paper examines the current application areas and future prospects of this technology. Challenges encountered in implementation underscore the need for further refinement of IoT technology. Despite these obstacles, experts contend that the crux lies not in issues of costs, standards, and techniques, but in the establishment of a viable business model in the SCM and logistics industries.

Exploring the Landscape: A Systematic Review on the Issues, Technologies, and Solutions related to the Integration of Blockchain with IoT

Over the past few years, the smart city concept has become a prominent solution to address urban challenges, including economic, social, and environmental issues. These cities strive to offer superior services in healthcare, energy management, transportation, and education by leveraging IoT devices. These devices are pivotal in data collection, analysis, and facilitating citizen interactions. Incorporating IoT applications into our surroundings augments automation, efficiency, and user comfort. To achieve this vision, it is imperative to ensure robust security, privacy, effective deployment, authentication, and resilience against cyber-attacks. Several recent studies have shown promising results regarding the use of blockchain for addressing IoT security concerns, especially in access control and authentication domains. The smart city concept, while beneficial, still faces numerous challenges regarding information security and privacy. With its unique characteristics like auditability, immutability, transparency, and decentralization, blockchain can significantly boost the growth of smart cities and rectify communication issues among IoT devices. This research explores blockchain\'s potential to resolve access control and authentication challenges in IoT when merged with it. It will also offer an in-depth analysis and evaluation of recently proposed solutions in the literature focusing on integrating IoT with blockchain.

CSR Evolution: New Opportunities and Challenges for IoT in Advancing ESG Practices

CSR Evolution: New Opportunities and Challenges for IoT in Advancing ESG Practices

Industrial Internet of Things: An Analysis of Emergence, Component and Challenges

Industry 4.0 brought a solution to disrupted industrial manufacturing powered by AI, machine learning, IoT, Cloud Computing, and Wireless Technologies. The factories turn into smart industrial units where the processes are automated, self-reliant, continuously monitored, and scaled as per the observed conditions. The Industrial Internet of Things (IIoT) solves the issues by real- time decision making or even alarming the hazardous situations say breaking down of systems or processes based on predictive analytics. From the raw material to the customer satisfaction the whole production line turns intelligent making the production fast, quality-based, well maintained, monitored, and innovative. The 3D printing, simulation, and augmented reality encourage innovations, designing & testing of customized products in the virtual environment. Big data analytics and accurate prediction not only foster manufacturing quality & quantity but also attracts high-valued staff with increased efficiency. Getting trustworthy data in real-time and eliminating life hazards in monitoring the typical processes are the key attractions of Industry 4.0 for instance, IoT with different kinds of sensors replace human monitoring and even performs well where the humans cannot go like the radioactive, humidity pressure. The product is tested well, safer to use, and promoted to the areas predicted by the advanced computing algorithms in data analytics. However, emerging technology can pose challenges for employers in a country where unemployment exists. So technological advancements, training, and skill developments are urgent areas to look after. This paper presented literature survey focuses on the major components, characteristics and associated challenges of Industrial IoT.

Exploring Machine Learning Intrusion Detection: Addressing Security and Privacy Challenges in IoT - A Comprehensive Review

With billions of IoT devices in operation globally, vast amounts of data are generated, posing significant security challenges throughout the data lifecycle. Machine learning (ML) offers a promising approach to safeguarding IoT systems by swiftly detecting anomalies and enforcing real-time security and privacy (S&P) measures. This systematic literature review investigates ML-based intrusion detection in IoT, examining academic journals from 2011 to 2021 through the IEEE and ProQuest databases. Utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, we identify key insights and challenges. Our review reveals that while ML-based Intrusion Detection Systems (IDS) exhibit superior performance in detecting emerging attack trends, they also introduce complexities such as increased computational demands, susceptibility to adversarial attacks, scalability issues, and trade-offs between accuracy and false positives. Furthermore, deep learning methods outperform traditional ML techniques in anomaly detection. Addressing the evolving nature of attacks remains a continuous endeavor, underscoring the ongoing development of IDS.

Progression and Challenges of IoT in Healthcare: A Short Review

Progression and Challenges of IoT in Healthcare: A Short Review

Hybrid Approaches (ABAC and RBAC) Toward Secure Access Control in Smart Home IoT

Smart homes are interconnected homes in which a wide variety of digital devices with limited resources communicate with multiple users and among themselves using multiple protocols. The deployment of resource-limited devices and the use of a wide range of technologies expand the attack surface and position the smart home as a target for many potential security threats. Access control is among the top security challenges in smart home IoT. Several access control models have been developed or adapted for IoT in general, with a few specifically designed for the smart home IoT domain. Most of these models are built on the role-based access control (RBAC) model or the attribute-based access control (ABAC) model. However, recently some researchers demonstrated that the need arises for a hybrid model combining ABAC and RBAC, thereby incorporating the benefits of both models to better meet IoT access control challenges in general and smart homes requirements in particular. In this paper, we used two approaches to develop two different hybrid models for smart home IoT. We followed a role-centric approach and an attribute-centric approach to develop HyBAC <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$_{RC}$</tex-math></inline-formula> and HyBAC <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$_{AC}$</tex-math></inline-formula> , respectively. We formally define these models and illustrate their features through a use case scenario demonstration. We further provide a proof-of-concept implementation for each model in Amazon Web Services (AWS) IoT platform. Finally, we conduct a theoretical comparison between the two models proposed in this paper in addition to the EGRBAC model (RBAC model for smart home IoT) and HABAC model (ABAC model for smart home IoT), which were previously developed to meet smart homes' challenges.

Current Trends and Challenges of IoT Next 5 Years

The world is moving forward at smart, and the credit goes to ever growing technology. One such concept is IOT (Internet of things) with which automation is no longer a virtual reality. IOT connects various physical objects through the internet and enables them to share information with their community network to automate processes for humans and makes their lives easier and comfortable. The paper presents the current trends and future challenges of IoT next 5 years, such as the technical, business and legal challenges.

A Formal Verification of a Reputation Multi-Factor Authentication Mechanism for Constrained Devices and Low-Power Wide-Area Network Using Temporal Logic.

There are many security challenges in IoT, especially related to the authentication of restricted devices in long-distance and low-throughput networks. Problems such as impersonation, privacy issues, and excessive battery usage are some of the existing problems evaluated through the threat modeling of this work. A formal assessment of security solutions for their compliance in addressing such threats is desirable. Although several works address the verification of security protocols, verifying the security of components and their non-locking has been little explored. This work proposes to analyze the design-time security of the components of a multi-factor authentication mechanism with a reputation regarding security requirements that go beyond encryption or secrecy in data transmission. As a result, it was observed through temporal logic that the mechanism is deadlock-free and meets the requirements established in this work. Although it is not a work aimed at modeling the security mechanism, this document provides the necessary details for a better understanding of the mechanism and, consequently, the process of formal verification of its security properties.

Current Trends and Challenges of IOT Next 5 Years

bstract: The world is moving forward at smart , and the credit goes to ever growing technology. One such concept is IOT (Internet of things) with which automation is no longer a virtual reality. IOT connects various physical objects through the internet and enables them to share information with their community network to automate processes for humans and makes their lives easier and confortable . The paper presents the current trends and future challenges of IoT next 5 years , such as the technical, business and legal challenges.

IoT applications and challenges in smart cities and services

AbstractInternet of Things (IoT) is a revolutionary and novel platform where a smart network connects to the large number of electronic devices via internet through available communication systems for reliable and real time connectivity, sensing thus acquiring data from sensors, computing and actuating devices. A review of the current status of IoT features, architecture, communication infrastructure and applications is presented here. Number of IoT applications and challenges in the development of smart cities are covered about this innovative technological platform in this review along with communication protocols characteristics and applications. IoT aided smart city services, health applications, transport applications and smart grid improvements are also discussed. Many challenges and issues related to security, communication, applications and system architecture along with future directions of IoT technology are elaborated in detail.

Internet of Things in Telecommunications: From the Perspective of an Emerging Market

This paper presents an exploratory case study of the Internet of things in telecommunications to analyze IoT technology in the telecom sector. It examines the IoT value in telecom and discusses the role of telecom operators across the value chain. It also presents a case analysis of IoT adoption in an emerging market of Pakistan to explore the IoT landscape in Pakistan and analyzes the IoT market positioning among telecom operators. It presents the business models and strategies which the telecom operators are following and analyzes the cost and benefits of IoT technology. It also discusses the IoT challenges faced by telecom operators during the adoption of IoT. In an emerging country like Pakistan, telecoms are adopting Internet of things technology, a novel, and real-time phenomenon. They are considering IoT technology as a new business opportunity in emerging markets, with the potential to be utilized as a new source of revenue. Telecoms are focusing on testing their roles in different areas of the IoT value chain. Their primary focus still remains basic connectivity which is evolved into smart connectivity. Telecoms are embracing their resources and capabilities across the IoT value chain, from connectivity to partnership, with innovative, value-added services. They are moving up to the IoT value chain by evolving further as an enabler for devices and enterprise-to-enterprise (E2E) solutions. They are developing partnerships with enterprises for providing various applications, service delivery, and system integration.

Analysis of Mechanisms for Resource Management in IoT: Performance of Mutual Authentication in the Context of Fog and EDGE-Fog Computing

The Internet is now experiencing an unprecedented expansion with the development of connected objects. At its inception the IoT, like any revolution, its objectives were quite limited. Its main objective was to reduce the effort of human data entry in order to allow the storage and automatic processing of the latter. Moreover, objects generate a lot of data that they cannot store or process by themselves, hence the need for external support. This is how Cloud Computing comes to answer this problem, making the success of IoT. This technology guarantees the storage, availability, processing, etc. of data, its integration into the latter is known as "Cloud of Things" CoT. The data generated should not only be stored, but rather processed in order to derive knowledge, decision making. The objective of our work is to analyze mutual authentication management models of IoT devices to optimize resources trying to provide solutions in the face of resource availability. To carry out this work, we analyzed the application areas and the challenges of IoT. Then, we studied IoT security threats. Our work ends with a study and an analysis mechanism of mutual authentication management models of IoT based on uncertificated Authentication mechanisms, Elliptic curve cryptography authentication, Mutual Authentication in the context of Fog Computing.