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IoT, Volume 2, Issue 1 (March 2021) – 10 articles

Cover Story (view full-size image): The IoT is transforming ordinary physical objects around us into an ecosystem of information that will enrich our lives. The key to this ecosystem is cooperation among devices, where things look for other things to provide composite services for the benefit of human beings. However, cooperation among nodes can only arise when nodes trust the information received by any other peer in the system. Previous efforts on trust were concentrated on proposing models and algorithms to manage the level of trustworthiness. In this paper, we focus on modeling the interaction between trustor and trustee in the IoT and on proposing guidelines to efficiently design trust management models. View this paper.
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Article
An Agent-Based Model of Task-Allocation and Resource-Sharing for Social Internet of Things
IoT 2021, 2(1), 187-204; https://0-doi-org.brum.beds.ac.uk/10.3390/iot2010010 - 23 Mar 2021
Viewed by 765
Abstract
The things in the Internet of Things are becoming more and more socially aware. What social means for these things (more often termed as “social objects”) is predominately determined by how and when objects interact with each other. In this paper, an agent-based [...] Read more.
The things in the Internet of Things are becoming more and more socially aware. What social means for these things (more often termed as “social objects”) is predominately determined by how and when objects interact with each other. In this paper, an agent-based model for Social Internet of Things is proposed, which features the realization of various interaction modalities, along with possible network structures and mobility modes, thus providing a novel model to ask interesting “what-if” questions. The scenario used, which is the acquisition of shared resources in a common spatial and temporal world, demands agents to have ad-hoc communication and a willingness to cooperate with others. The model was simulated for all possible combinations of input parameters to study the implications of competitive vs. cooperative social behavior while agents try to acquire shared resources/services in a peer-to-peer fashion. However, the main focus of the paper was to analyze the impact of profile-based mobility, which has an underpinning on parameters of extent and scale of a mobility profile. The simulation results, in addition to others, reveal that there are substantial and systematic differences among different combinations of values for extent and scale. Full article
(This article belongs to the Special Issue The Leverage of Social Media and IoT)
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Article
Cyber Threats to Industrial IoT: A Survey on Attacks and Countermeasures
IoT 2021, 2(1), 163-186; https://0-doi-org.brum.beds.ac.uk/10.3390/iot2010009 - 07 Mar 2021
Cited by 1 | Viewed by 1585
Abstract
In today’s Industrial Internet of Things (IIoT) environment, where different systems interact with the physical world, the state proposed by the Industry 4.0 standards can lead to escalating vulnerabilities, especially when these systems receive data streams from multiple intermediaries, requiring multilevel security approaches, [...] Read more.
In today’s Industrial Internet of Things (IIoT) environment, where different systems interact with the physical world, the state proposed by the Industry 4.0 standards can lead to escalating vulnerabilities, especially when these systems receive data streams from multiple intermediaries, requiring multilevel security approaches, in addition to link encryption. At the same time taking into account the heterogeneity of the systems included in the IIoT ecosystem and the non-institutionalized interoperability in terms of hardware and software, serious issues arise as to how to secure these systems. In this framework, given that the protection of industrial equipment is a requirement inextricably linked to technological developments and the use of the IoT, it is important to identify the major vulnerabilities and the associated risks and threats and to suggest the most appropriate countermeasures. In this context, this study provides a description of the attacks against IIoT systems, as well as a thorough analysis of the solutions for these attacks, as they have been proposed in the most recent literature. Full article
(This article belongs to the Special Issue Cyber Security and Privacy in IoT)
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Article
IoT Traffic: Modeling and Measurement Experiments
IoT 2021, 2(1), 140-162; https://0-doi-org.brum.beds.ac.uk/10.3390/iot2010008 - 26 Feb 2021
Viewed by 1173
Abstract
We now use the Internet of things (IoT) in our everyday lives. The novel IoT devices collect cyber–physical data and provide information on the environment. Hence, IoT traffic will count for a major part of Internet traffic; however, its impact on the network [...] Read more.
We now use the Internet of things (IoT) in our everyday lives. The novel IoT devices collect cyber–physical data and provide information on the environment. Hence, IoT traffic will count for a major part of Internet traffic; however, its impact on the network is still widely unknown. IoT devices are prone to cyberattacks because of constrained resources or misconfigurations. It is essential to characterize IoT traffic and identify each device to monitor the IoT network and discriminate among legitimate and anomalous IoT traffic. In this study, we deployed a smart-home testbed comprising several IoT devices to study IoT traffic. We performed extensive measurement experiments using a novel IoT traffic generator tool called IoTTGen. This tool can generate traffic from multiple devices, emulating large-scale scenarios with different devices under different network conditions. We analyzed the IoT traffic properties by computing the entropy value of traffic parameters and visually observing the traffic on behavior shape graphs. We propose a new method for identifying traffic entropy-based devices, computing the entropy values of traffic features. The method relies on machine learning to classify the traffic. The proposed method succeeded in identifying devices with a performance accuracy up to 94% and is robust with unpredictable network behavior with traffic anomalies spreading in the network. Full article
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Article
CNN-Based Smart Sleep Posture Recognition System
IoT 2021, 2(1), 119-139; https://0-doi-org.brum.beds.ac.uk/10.3390/iot2010007 - 24 Feb 2021
Viewed by 947
Abstract
Sleep pattern and posture recognition have become of great interest for a diverse range of clinical applications. Autonomous and constant monitoring of sleep postures provides useful information for reducing the health risk. Prevailing systems are designed based on electrocardiograms, cameras, and pressure sensors, [...] Read more.
Sleep pattern and posture recognition have become of great interest for a diverse range of clinical applications. Autonomous and constant monitoring of sleep postures provides useful information for reducing the health risk. Prevailing systems are designed based on electrocardiograms, cameras, and pressure sensors, which are not only expensive but also intrusive in nature, and uncomfortable to use. We propose an unobtrusive and affordable smart system based on an electronic mat called Sleep Mat-e for monitoring the sleep activity and sleep posture of individuals living in residential care facilities. The system uses a pressure sensing mat constructed using piezo-resistive material to be placed on a mattress. The sensors detect the distribution of the body pressure on the mat during sleep and we use convolution neural network (CNN) to analyze collected data and recognize different sleeping postures. The system is capable of recognizing the four major postures—face-up, face-down, right lateral, and left lateral. A real-time feedback mechanism is also provided through an accompanying smartphone application for keeping a diary of the posture and send alert to the user in case there is a danger of falling from bed. It also produces synopses of postures and activities over a given duration of time. Finally, we conducted experiments to evaluate the accuracy of the prototype, and the proposed system achieved a classification accuracy of around 90%. Full article
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Article
Process Automation in an IoT–Fog–Cloud Ecosystem: A Survey and Taxonomy
IoT 2021, 2(1), 92-118; https://0-doi-org.brum.beds.ac.uk/10.3390/iot2010006 - 07 Feb 2021
Cited by 4 | Viewed by 1453
Abstract
The number of IoT sensors and physical objects accommodated on the Internet is increasing day by day, and traditional Cloud Computing would not be able to host IoT data because of its high latency. Being challenged of processing all IoT big data on [...] Read more.
The number of IoT sensors and physical objects accommodated on the Internet is increasing day by day, and traditional Cloud Computing would not be able to host IoT data because of its high latency. Being challenged of processing all IoT big data on Cloud facilities, there is not enough study on automating components to deal with the big data and real-time tasks in the IoT–Fog–Cloud ecosystem. For instance, designing automatic data transfer from the fog layer to cloud layer, which contains enormous distributed devices is challenging. Considering fog as the supporting processing layer, dealing with decentralized devices in the IoT and fog layer leads us to think of other automatic mechanisms to manage the existing heterogeneity. The big data and heterogeneity challenges also motivated us to design other automatic components for Fog resiliency, which we address as the third challenge in the ecosystem. Fog resiliency makes the processing of IoT tasks independent to the Cloud layer. This survey aims to review, study, and analyze the automatic functions as a taxonomy to help researchers, who are implementing methods and algorithms for different IoT applications. We demonstrated the automatic functions through our research in accordance to each challenge. The study also discusses and suggests automating the tasks, methods, and processes of the ecosystem that still process the data manually. Full article
(This article belongs to the Special Issue The Leverage of Social Media and IoT)
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Review
Post-Quantum Cryptosystems for Internet-of-Things: A Survey on Lattice-Based Algorithms
IoT 2021, 2(1), 71-91; https://0-doi-org.brum.beds.ac.uk/10.3390/iot2010005 - 05 Feb 2021
Viewed by 1373
Abstract
The latest quantum computers have the ability to solve incredibly complex classical cryptography equations particularly to decode the secret encrypted keys and making the network vulnerable to hacking. They can solve complex mathematical problems almost instantaneously compared to the billions of years of [...] Read more.
The latest quantum computers have the ability to solve incredibly complex classical cryptography equations particularly to decode the secret encrypted keys and making the network vulnerable to hacking. They can solve complex mathematical problems almost instantaneously compared to the billions of years of computation needed by traditional computing machines. Researchers advocate the development of novel strategies to include data encryption in the post-quantum era. Lattices have been widely used in cryptography, somewhat peculiarly, and these algorithms have been used in both; (a) cryptoanalysis by using lattice approximation to break cryptosystems; and (b) cryptography by using computationally hard lattice problems (non-deterministic polynomial time hardness) to construct stable cryptographic functions. Most of the dominant features of lattice-based cryptography (LBC), which holds it ahead in the post-quantum league, include resistance to quantum attack vectors, high concurrent performance, parallelism, security under worst-case intractability assumptions, and solutions to long-standing open problems in cryptography. While these methods offer possible security for classical cryptosytems in theory and experimentation, their implementation in energy-restricted Internet-of-Things (IoT) devices requires careful study of regular lattice-based implantation and its simplification in lightweight lattice-based cryptography (LW-LBC). This streamlined post-quantum algorithm is ideal for levelled IoT device security. The key aim of this survey was to provide the scientific community with comprehensive information on elementary mathematical facts, as well as to address real-time implementation, hardware architecture, open problems, attack vectors, and the significance for the IoT networks. Full article
(This article belongs to the Special Issue Cyber Security and Privacy in IoT)
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Article
A Binary Trust Game for the Internet of Things
IoT 2021, 2(1), 50-70; https://0-doi-org.brum.beds.ac.uk/10.3390/iot2010004 - 27 Jan 2021
Viewed by 992
Abstract
The IoT is transforming the ordinary physical objects around us into an ecosystem of information that will enrich our lives. The key to this ecosystem is the cooperation among the devices, where things look for other things to provide composite services for the [...] Read more.
The IoT is transforming the ordinary physical objects around us into an ecosystem of information that will enrich our lives. The key to this ecosystem is the cooperation among the devices, where things look for other things to provide composite services for the benefit of human beings. However, cooperation among nodes can only arise when nodes trust the information received by any other peer in the system. Previous efforts on trust were concentrated on proposing models and algorithms to manage the level of trustworthiness. In this paper, we focus on modelling the interaction between trustor and trustee in the IoT and on proposing guidelines to efficiently design trust management models. Simulations show the impacts of the proposed guidelines on a simple trust model. Full article
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Article
Sensing and Forecasting Crowd Distribution in Smart Cities: Potentials and Approaches
IoT 2021, 2(1), 33-49; https://0-doi-org.brum.beds.ac.uk/10.3390/iot2010003 - 08 Jan 2021
Cited by 2 | Viewed by 1338
Abstract
The possibility of sensing and predicting the movements of crowds in modern cities is of fundamental importance for improving urban planning, urban mobility, urban safety, and tourism activities. However, it also introduces several challenges at the level of sensing technologies and data analysis. [...] Read more.
The possibility of sensing and predicting the movements of crowds in modern cities is of fundamental importance for improving urban planning, urban mobility, urban safety, and tourism activities. However, it also introduces several challenges at the level of sensing technologies and data analysis. The objective of this survey is to overview: (i) the many potential application areas of crowd sensing and prediction; (ii) the technologies that can be exploited to sense crowd along with their potentials and limitations; (iii) the data analysis techniques that can be effectively used to forecast crowd distribution. Finally, the article tries to identify open and promising research challenges. Full article
(This article belongs to the Special Issue Internet of Things Technologies for Smart Cities)
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Article
Testing an “IoT” Tide Gauge Network for Coastal Monitoring
IoT 2021, 2(1), 17-32; https://0-doi-org.brum.beds.ac.uk/10.3390/iot2010002 - 08 Jan 2021
Cited by 1 | Viewed by 1213
Abstract
A low-cost “Internet of Things” (IoT) tide gauge network was developed to provide real-time and “delayed mode” sea-level data to support monitoring of spatial and temporal coastal morphological changes. It is based on the Arduino Sigfox MKR 1200 micro-controller platform with a Measurement [...] Read more.
A low-cost “Internet of Things” (IoT) tide gauge network was developed to provide real-time and “delayed mode” sea-level data to support monitoring of spatial and temporal coastal morphological changes. It is based on the Arduino Sigfox MKR 1200 micro-controller platform with a Measurement Specialties pressure sensor (MS5837). Experiments at two sites colocated with established tide gauges show that these inexpensive pressure sensors can make accurate sea-level measurements. While these pressure sensors are capable of ~1 cm accuracy, as with other comparable gauges, the effect of significant wave activity can distort the overall sea-level measurements. Various off-the-shelf hardware and software configurations were tested to provide complementary data as part of a localized network and to overcome operational constraints, such as lack of suitable infrastructure for mounting the tide gauges and for exposed beach locations. Full article
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Article
Decentralized Actionable Cyber Threat Intelligence for Networks and the Internet of Things
IoT 2021, 2(1), 1-16; https://0-doi-org.brum.beds.ac.uk/10.3390/iot2010001 - 30 Dec 2020
Viewed by 1608
Abstract
Security presents itself as one of the biggest threats to the enabling and the deployment of the Internet of Things (IoT). Security challenges are evident in light of recent cybersecurity attacks that targeted major internet service providers and crippled a significant portion of [...] Read more.
Security presents itself as one of the biggest threats to the enabling and the deployment of the Internet of Things (IoT). Security challenges are evident in light of recent cybersecurity attacks that targeted major internet service providers and crippled a significant portion of the entire Internet by taking advantage of faulty and ill-protected embedded devices. Many of these devices reside at home networks with user-administrators who are not familiar with network security best practices, making them easy targets for the attackers. Therefore, security solutions are needed to navigate the insecure and untrusted public networks by automating protections through affordable and accessible first-hand network information sharing. This paper proposes and implements a proof of concept (PoC) to secure Internet Service Providers (ISPs), home networks, and home-based IoT devices using blockchain technologies. The results obtained support the idea of a distributed cyber threat intelligence data sharing network capable of protecting various stakeholders. Full article
(This article belongs to the Special Issue Cyber Security and Privacy in IoT)
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