A Comparative Study of Post-Quantum Cryptographic Algorithm Implementations for Secure and Efficient Energy Systems Monitoring

Since the Internet of Things (IoT) will be entwined with everything we use in our daily life, the consequence of security flaws escalates. Smart objects will govern most of the home appliances and car engines yielding potential disaster scenarios. In this context, successful attacks could lead to chaos and scary scenarios (www.darkreading.com). Unprotected personal information may expose sensitive and embarrassing data to the public and attacks may threaten not only our computers and smart devices, but our intimacy and perhaps our lives too. Because persons and objects will be bonded with each other, user consent becomes critical. Therefore, thing, object, and user Identity will be the focus of future IoT security solutions, yielding a Trust, Security, and Privacy (TSP) paradigm, which may constitute the Achilles' heel of IoT. While security issues are quite straightforward, mainly from background knowledge, privacy issues are far more complex. Privacy constitutes a rather challenging task, even for the m...

LoRaWAN based internet of things (IoT) system for precision irrigation in plasticulture fresh-market tomato

The Internet of Things (IoT) has revolutionised the way people live and work, and its increasing popularity has led to the widespread adoption of smart homes. However, the lack of interoperability among IoT devices and systems used in smart homes limits their capacity to enhance the user experience and improve energy efficiency. Therefore, this study focuses on improving interoperability between various IoT systems and devices. It was anticipated that the research would contribute to the creation of a more cohesive and integrated smart home environment by helping to develop a data analytics framework that enables the integration and analysis of data from various devices. The study then produces an intended user design strategy for smart homes that takes into account users' wants, preferences, and behaviours during the design phase. The goal of this project was to create smart houses that are more intelligent, environmentally green, and user-friendly and that will benefit both individuals and the whole society.

Herein, an Internet of Things (IoT) system with remote reconfigurable wireless sensor network (WSN) nodes is presented and its application to measure group work activity in a classroom is discussed. This IoT system consists of wiki pages, bots, (defined as remotely controlled devices), gateways, and remotely reconfigurable WSN Nodes. The bots/gateways and WSN nodes of the IoT system are controlled by scripts written on wiki pages that are read by the bot/gateways, which then forward the commands contained in the scripts to the WSN nodes. Each WSN node then executes the commands, obtains the resulting sensor values, and then returns those values to the bot/gateways. The bot/gateways relay the values and write them onto the wiki page. Each WSN node is flexible and reconfigurable because its behavior can be changed by the script commands written onto the wiki page. Using this IoT system, we created a measurement system to evaluate activity levels of group work in a classroom. After developing the measurement system, we found it was possible to adjust the sampling rate for obtaining sensor values simply by rewriting the script on the wiki page without directly manipulating the WSN.

Privacy preservation in blockchain based IoT systems: Integration issues, prospects, challenges, and future research directions

Internet of Things (IoT) systems are characterized by being highly heterogeneous, distributed, and scalable, made up of a variety of devices that operate in uncertain and ubiquitous settings. In this sense, models@runtime emerges as a promising software development approach to address IoT systems’ intrinsic characteristics. This study presents a systematic review to know the state of the art using of models@runtime to support IoT systems’ operation. The methodology proposed by Kitchenham has been used to carry out this research. The systematic review answers the following research questions: i) How are models@runtime being used in the IoT domain? And ii) How is addressed the research in studies related to the use of models@runtime in the IoT domain? Initially, 692 primary studies were retrieved, where 50 relevant studies related to approaches based on models@runtime for IoT were selected after applying the corresponding inclusion and exclusion criteria. Those primary studies were classified based on the extraction criteria. Among review’s main results are that the models@runtime have been widely used to support the monitoring and self-adaptation mechanisms in IoT systems, as opposed to the few studies found aimed at interoperability, quality assurance, self-organization, and self-optimization of IoT systems, consisting of essential research opportunities.

Engineering Internet of Things (IoT) systems is a challenging task partly due to the dynamicity and uncertainty of the environment including the involvement of the human in the loop. Users should be able to achieve their goals seamlessly in different environments, and IoT systems should be able to cope with dynamic changes. Several approaches have been proposed to enable the automated formation, enactment, and self-adaptation of goal-driven IoT systems. However, they do not address deployment issues. In this paper, we propose a goal-driven approach for deploying self-adaptive IoT systems in the Edge-Cloud continuum. Our approach supports the systems to cope with the dynamicity and uncertainty of the environment including changes in their deployment topologies, i.e., the deployment nodes and their interconnections. We describe the architecture and processes of the approach and the simulations that we conducted to validate its feasibility. The results of the simulations show that the approach scales well when generating and adapting the deployment topologies of goal-driven IoT systems in smart homes and smart buildings.

The Internet of Things (IoT) systems usually use constrained devices with limited computation and communication resources facilitating the use of lightweight communication protocols. Message Queue Telemetry Transport (MQTT) is a lightweight publish-subscribe-based messaging protocol that works on top of the TCP/IP protocol. We present our progress towards building a simulation tool for evaluating the Quality of Service (QoS) in MQTT-based IoT systems. This tool can facilitate the design of IoT systems that need to meet certain QoS requirements.

This chapter discusses the architecture of Internet of Things (IoT) systems. IoT system security takes a team of experts in network security, computer security, hardware and software security, cloud infrastructure security, secure protocols, and cryptography. The security of an IoT system is extremely complex and crosses many security disciplines. Various industries and standards groups have developed and proliferated system architectures in order to better communicate the issues and requirements relating to systems for which they are concerned. The Internet of Things community is no different from any other architectural community. The primary difference is that IoT spans many different industries and ecosystems, and has a diverse set of concerns. The cloud is essential to an IoT system because it houses centralized applications and contains the data model of the IoT system, making those applications accessible to its users wherever they are, and is wholly independent of the actual location of the IoT devices themselves.

A survey of trust computation models for service management in internet of things systems

PurposeThe purpose of this paper is to answer “Why do Chinese consumers use IOT systems?” and “Do consumers’ cognitive and affect experiences moderate the relationship between psychological perception factors and perceived usefulness?”Design/methodology/approachIn-depth interview with consumers and experts had been conducted and then the perceived psychological factors that influence perceived usefulness had been summarized. Based on a survey test of 337 smart home users, this study applies partial least squares technique analysis to test the research model.FindingsThe research results show that perceived psychological factors (perceived ease of use, perceived intelligence, perceived convenience and perceived privacy risk) have significant effect on the intention and behavior of IOT systems usage through perceived usefulness. Cognitive experience moderates the relationship between perceived ease of use and perceived usefulness, perceived privacy risk and perceived usefulness; affect experience moderates the relationship between perceived ease of use and perceived usefulness.Research limitations/implicationsThe current study mainly tested the antecedents of consumers’ usage of IOT systems, and the outcome of using the system was not investigated. Future research can examine the outcome (e.g. satisfaction, perceived value) by using the expectation-confirmation theory.Originality/valueThis study provides a useful insight into the key driving factors in consumers’ intention and behavior of using IOT systems. The previous studies over IOT systems have not observed consumers’ perception of IOT systems, but in fact IOT systems are being applied to more and more personal users.

Advanced digital signatures for preserving privacy and trust management in hierarchical heterogeneous IoT: Taxonomy, capabilities, and objectives

Wireless communication in Internet of Things (IoT) systems involves several devices communicating in the limited available frequency spectrum using different wireless communication standards. To achieve efficient spectrum usage in the IoT systems, it is desired to have the ability of dynamic spectrum allocation. Cognitive radios (CR) enable efficient spectrum utilization by performing spectrum sensing to gain the knowledge of current spectrum occupancy and dynamically reconfiguring the communication parameters, making them highly suitable for IoT systems. In this paper, we present the efficient hardware implementation of a spectrum sensing scheme for CR based IoT applications that require large bandwidth. We show that the proposed implementation on field programmable gate arrays (FPGAs) can achieve over 1.56x improvement in performance, while consuming 77% less generic resources and at a fractionally higher power consumption.

With the continuous development of the Internet of Things (IoT) and the needs of the times, the number of IoT edge devices is rapidly increasing, and to be able to provide users with more reliable information services and decision-making, this paper constructs an IoT system based on cloud-edge collaboration. Based on cloud-edge collaboration, data mining technology is used to categorize data, and regression models and branch neural networks are combined to further improve the IoT system based on cloud-edge collaboration. Finally, the particle swarm algorithm is used to optimize reinforcement learning, and the framework of an IoT system built on cloud-edge partnership is established. Through the data processing experiments on IoT edge computing, the data mining performance of the IoT edge computing-based data mining method is improved by 0.0295, 0.1870, and 0.2059 on the large datasets of Dataset4 and Dataset5, respectively. the average turnaround time is lower than 6.5 for different edge computing power levels. The system rewards are gradually improved from 5.3 to 8.2, and the number of packet loss of the algorithm is less than 5. The feasibility and effectiveness of the IoT data mining method and system based on cloud-edge collaboration are confirmed by this study, and a feasible method for data mining can be applied to IoT systems under cloud-edge collaboration.

Computational notebooks to support developers in prototyping IoT systems