An OWL-S based specification model of dynamic entity services for IoT

Security vulnerabilities of the modern Internet of Things (IoT) systems are unique, mainly due to the complexity and heterogeneity of the technology and data. The risks born out of these IoT systems cannot easily fit into an existing risk framework. There are many cybersecurity risk assessment approaches and frameworks that are under deployment in many governmental and commercial organizations. Extending these existing frameworks to IoT systems alone will not address the new risks that have arisen in the IoT ecosystem. This study has included a review of existing popular cyber risk assessment methodologies and their suitability to IoT systems. National Institute of Standards and Technology, Operationally Critical Threat, Asset, and Vulnerability Evaluation, Threat Assessment & Remediation Analysis, and International Standards Organization are the four main frameworks critically analyzed in this research study. IoT risks are presented and reviewed in terms of the IoT risk category and impacted industries. IoT systems in financial technology and healthcare are dealt with in detail, given their high-risk exposure. Risk vectors for IoT and the Internet of Medical Things (IoMT) are discussed in this study. A unique risk ranking method to rank and quantify IoT risk is introduced in this study. This ranking method initiates a risk assessment approach exclusively for IoT systems by quantifying IoT risk vectors, leading to effective risk mitigation strategies and techniques. A unique computational approach to calculate the cyber risk for IoT systems with IoT-specific impact factors has been designed and explained in the context of IoMT systems.

The demand for IoT (Internet of Things) systems that encompass cloud computing, the multitude of low power sensing and data collection electronic devices and distributed communications architecture is increasing at an exponential pace. With increasing interests from different industrial, business and social groups, in the near future it will be necessary to support massive deployment of diverse IoT systems in different geographical areas. Large scale deployment of IoT systems will introduce challenging problems for the communication designers, as the networking is one of the key enabling technologies for the IoT systems. Major challenges include cost effective network architecture, support of large area of coverage and diverse QoS (Quality of Service) requirements, reliability, spectrum requirements, energy requirements, and many other related issues. The paper initially reviews different classes of IoT applications and their communication requirements. Following the review, different communications and networking technologies that can potentially support large scale deployment of IoT systems for different industrial, business and social applications are discussed. The paper then concentrates on wireless networking technologies for IoT systems with specific focus on deployment issues. The deployment discussion concentrates on different IoT systems QoS and networking requirements, cost, coverage area and energy supply requirements. We introduce a sustainable low cost heterogeneous network design using short range radio standards such as IEEE 802.15.4/Zigbee, IEEE 802.11/WLAN that can be used to develop a wide area networks to support large number of IoT devices for various applications. Finally the paper makes some general recommendations towards sustainable network design techniques for future IoT systems that can reduce the OPEX and CAPEX requirements.

Internet of Things (IoT) systems running on Microcontrollers (MCUS) have become a prominent target of remote attacks. Although deployed in security and safety critical domains, such systems lack basic mitigations against control-flow hijacking attacks. Attacks against IoT systems already enabled malicious takeover of smartphones, vehicles, unmanned aerial vehicles, and industrial control systems. The thesis introduces a systemic analysis of previous defense mitigations to secure IoT systems. Building off this systematization, we identify two main issues in IoT systems security. First, efforts to protect IoT systems are hindered by the lack of realistic benchmarks and evaluation frameworks. Second, existing solutions to protect from control-flow hijacking on the return edge are either impractical or have limited security guarantees. This thesis addresses these issues using two approaches. First, we present BenchIoT, a benchmark suite of five realistic IoT applications and an evaluation framework that enables automated and extensible evaluation of 14 metrics covering security, performance, memory usage, and energy. BenchIoT enables evaluating and comparing security mechanisms. Using BenchIoT, we show that even if two security mechanisms have similarly modest runtime overhead, one can have undesired consequences on security such as a large portion of privileged user execution. Second, we introduce Return Address Integrity (RAI), a novel security mechanism to prevent all control-flow hijacking attacks targeting return edges, without requiring special hardware. We design and implement μRAI to enforce the RAI property. Our results show μRAI has a low runtime overhead of 0.1% on average, and therefore is apractical solution for IoT systems. This thesis enables measuring the security IoT systems through standardized benchmarks and metrics. Using static analysis and runtime monitors, it prevents control-flow hijacking attacks on return edges with low runtime overhead. Combined, this thesis advances the state-of-the-art of protecting IoT systems and benchmarking its security.

Internet of Things (IoT) systems are becoming more and more popular. Moreover, service-based approach to IoT systems development is practically a standard utilized in their architecture. uti. IoT communication problems ware discussed in many articles about wireless communication, sensor networks or cloud computing. However the topic of high-level end to end communication in IoT systems is much less often the point of researchers’ interest. Despite that, the reliability of communication makes much more sense especially when it is considered at the application layer. Furthermore, networks utilized in IoT systems are usually virtual and software-based. Due to this fact, it is reasonable to take consider this problem with a novel and adequate approach, rather with classical models of communication resource allocation. In this article authors presented an idea of reliable communication management for IoT systems based on resource allocation. This idea is discussed in context of service-based IoT system lifecycle, especially considering the stages of resource allocation and services execution. Concerning the presented concept, three algorithms were prepared and tested in the simulation process.

User experience key performance indicators for industrial IoT systems: A multivocal literature review

The apparent growth of the internet of things (IoT) has allowed its deployment in many domains. The IoT devices sense their surroundings and transmit the data via the Web. According to statistics, due to the proliferation of smart devices, the number of active IoT devices is expected to exceed 25.4 billion by 2030.1 A large number of IoT objects gather an enormous amount of raw data. The data generated by various IoT objects and sensors are heterogeneous, with varying types and formats. Therefore, it is difficult for IoT systems to share and reuse raw IoT data, which causes the problem of lack of interoperability. The lack of interoperability in IoT systems creates a problematic issue that prevents IoT systems from performing well. To address this issue, data modeling and knowledge representation using semantic web technologies may be an appropriate solution to give meaning to raw IoT data and convert it to an enriched data format. The primary goal of this research section is to highlight the best outcomes for semantic interoperability among IoT systems, which can serve as a guideline for future studies via the presentation of a literature review on semantic interoperability for Internet of Things systems, including challenges, prospects, and recent work. The paper also provides an overview of the application of semantic web technologies in IoT systems, such as specific ontologies, frameworks, and application domains that use semantic technologies in the IoT areas to solve interoperability and heterogeneity problems.

The heterogeneity of Internet of Things (IoT) systems has so far prevented the definition of adequate standards, hence making it difficult to compare meaningfully the security degree of diverse architectural choices. This task can be nonetheless achieved with formal methodologies. However, the dedicated IoT literature shows no evidence of a universal model allowing the security evaluation of any arbitrary system. Based on these considerations, we propose a new model that aims at being global and all-encompassing. Our model can be used to fairly analyse the security level of different IoT systems and compare them in a significant way. It is designed to be adaptive with realistic definitions of the adversary’s (1) actions of interacting with IoT systems; (2) capabilities of accessing the data generated by and exchanged in IoT systems with established rules; and (3) objectives of attacking IoT systems according to the four recognised security properties of confidentiality, integrity, availability and soundness. Such a design enables the straightforward characterization of new adversaries. It further helps in providing a fine-grained security evaluation of IoT systems by either accurately describing attacks against the analysed systems or formally proving their guaranteed level of security.

Internet of Things (IoT) systems are complex systems that can manage mission-critical, costly operations or the collection, storage, and processing of sensitive data. Therefore, security represents a primary concern that should be considered when engineering IoT systems. Additionally, several challenges need to be addressed, including the following ones. IoT systems’ environments are dynamic and uncertain. For instance, IoT devices can be mobile or might run out of batteries, so they can become suddenly unavailable. To cope with such environments, IoT systems can be engineered as goal-driven and self-adaptive systems. A goal-driven IoT system is composed of a dynamic set of IoT devices and services that temporarily connect and cooperate to achieve a specific goal. Several approaches have been proposed to engineer goal-driven and self-adaptive IoT systems. However, none of the existing approaches enable goal-driven IoT systems to automatically detect security threats and autonomously adapt to mitigate them. Toward bridging these gaps, this paper proposes a distributed architectural Approach for engineering goal-driven IoT Systems that can autonomously SElf-adapt to secuRity Threats in their environments (ASSERT). ASSERT exploits techniques and adopts notions, such as agents, federated learning, feedback loops, and blockchain, for maintaining the systems’ security and enhancing the trustworthiness of the adaptations they perform. The results of the experiments that we conducted to validate the approach’s feasibility show that it performs and scales well when detecting security threats, performing autonomous security adaptations to mitigate the threats and enabling systems’ constituents to learn about security threats in their environments collaboratively.

In this paper, we study a covert Internet of Things (IoT) system. Compared with conventional IoT systems that apply cryptography and information-theoretic secrecy approaches to secure the transmission, our considered IoT system adopts the covertness technique and intends to hide the legitimate transmission from the observant adversaries. In the IoT system, the IoT devices randomly transmit the collected data to their associated IoT gateways (GWs). In the meantime, the adversaries attempt to detect the existence of legitimate transmission based on their received signal power and launch hostile attacks accordingly. To avoid being detected by the adversaries, the IoT system applies uplink power control to achieve covert legitimate transmission. Moreover, to distort the observation of the adversaries so as to mislead their decisions, we propose an artificial noise (AN)-assisted covert communication design, where the AN is transmitted by in-band full-duplex (IBFD) IoT GWs as a jamming operation. We formulate a Stackelberg game to study the interaction between the adversaries and the legitimate entities including the IoT GWs and IoT devices, where the legitimate entities, as the leaders, decide on the powers of legitimate and AN transmissions at the upper level and the adversaries, as the followers, aim to minimize their detection errors at the lower level. Thereafter, considering the large scale of IoT system, we further cast the Stackelberg game into a mean-field Stackelberg game and incorporate the stochastic geometry and statistical channel model to capture the location heterogeneity and channel dynamics among and of the system entities, respectively. In the performance evaluation, we verify the practicability of the mean-field Stackelberg game. Moreover, we demonstrate the effectiveness of AN in improving the transmission covertness.

Internet of Things (IoT) systems are inherently built on data gathered from heterogeneous sources. In the quest to gather more data for better analytics, many IoT systems are instigating significant challenges. First, the sheer volume and velocity of data generated by IoT systems are burdening our networking infrastructure, especially at the edge. The mobility and intermittent connectivity of edge IoT nodes are further hampering real-time access and reporting of IoT data. As we attempt to synergize IoT systems to leverage resource discovery and remedy some of these challenges, the rising challenges of Quality of Information (QoI) and Quality of Resource (QoR) calibration, render many IoT interoperability attempts far-fetched. We survey a number of challenges in realizing IoT interoperability, and advocate for a uniform view of data management in IoT systems. We delve into three planes that encompass Big Sensed Data (BSD) research directions, presenting a building block for future research efforts in IoT data management.

Recently, Internet of Thing (IoT) systems enable an interconnection between systems, humans, and services to create an (autonomous) ecosystem of various computation-intensive things. Software architecture supports an effective modeling, specification, implementation, deployment, and maintenance of software-intensive things to engineer and operationalize IoT systems. In order to conceptualize and optimize the role of software architectures for IoTs, there is a dire need for research efforts to analyse the existing research and solutions to formulate the vision for futuristic research and development. In this research, we propose to empirically analyse and taxonomically classify the impacts of research on designing, architecting, and developing IoT-driven software systems. We have conducted a survey-based study of the existing research – investigating challenges, solutions and required futuristic efforts – on architecting IoT systems. The results of survey highlight that software architecture solutions support various research themes for IoT systems such as (i) cloud-based ecosystems, (ii) reference architectures, (ii) autonomous systems, and (iv) agent-based systems for IoT-based software. The results also indicate that any futuristic vision to architect IoT software should incorporate architectural processes, patterns, models and languages to support reusable, automated, and efficient development of IoTs. The proposed research documents structured and systemised knowledge about software architecture to develop IoT systems. Such knowledge can facilitate the researchers and developers to identify the key areas, understand the existing solution and their limitations to conceptualize and propose innovation solutions for existing and emerging challenges related to the development of IoT software.

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

What are IoT systems for real? An experts’ survey on software engineering aspects

The enthusiasm of IT entrepreneurs in producing Internet of Things (IoT) systems is undeniable as currently, the number of connected devices is enormously increasing. Many research has been done to efficiently develop IoT systems. IoT systems are usually engineered from scratch. IoT component models have been introduced but lack of generic development framework or model that supports high reusability and loose coupling in dealing with the heterogeneous devices that can hinder its development. Thus, an IoT component model is proposed. Meta-modelling has been used to define the component model where the specific interaction and composition standard in a component are abstracted. IoT component model is intended to develop a prototype for IoT development. With this IoT prototype, IoT system developers will not need to develop everything from scratch every time, as generic components can be reused even when it is applied in different domains or during system enhancement is required. Smart home IoT system has been selected as a case study to evaluate our prototype tool. In this study, we provide an alternative way to develop IoT software in component-based software engineering method. A prototype has also been developed to assist reusability and reduce coupling between modules.

Internet of things (IoT) systems are composed of variety of units from different domains. While developing a complete IoT system, different professionals from different domains may have to work in collaboration. In this paper we provide a framework which allows using discrete and continuous time modeling and simulation approaches in combination for IoT systems. The proposed framework demonstrates on how to model Ad-hoc and general IoT systems for software engineering purpose. We demonstrate that model-based software engineering on one hand can provide a common platform to overcome communication gaps among collaborating stakeholders whereas, on the other hand can model and integrate heterogeneous components of IoT systems. While modeling heterogeneous IoT systems, one of the major challenges is to apply continuous and discrete time modeling on intrinsically varying components of the system. Another difficulty may be how to compose these heterogeneous components into one whole system. The proposed framework provides a road-map to model discrete, continuous, Ad-hoc, general systems along with composition mechanism of heterogeneous subsystems. The framework uses a combination of Agent-based modeling, Aspect-oriented modeling, contract-based modeling and services-oriented modeling concepts. We used this framework to model a scenario example of a service-oriented IoT system as proof of concept. We analyzed our framework with existing systems and discussed it in details. Our framework provides a mechanism to model different viewpoints. The framework also enhances the completeness and consistency of the IoT software models.