IoT Ecosystem Research Articles

Value creation system in the connected home ecosystem

The creation of value in the IoT ecosystems of the connected home has for years been a topic of interest for the white goods industry; however, the limitations of information of the new technologies have been a barrier to the adoption of these ecosystems, in this sense, this research aims to model the behavior of the value creation system in the connected home ecosystem. With this in mind, through a prospective study, the system was modeled and the key variables identified, that is, variables on which efforts should be focused in the medium term. Subsequently, as no theoretical method is known to model the problem, it was applied fuzzy logic and dynamic systems to understand the behavior of value creation in the ecosystem. Last a mathematical formula is proposed to estimate value creation. It is discovered in the analysis of results that the correct combination of technologies is a relevant point for the creation of value, as well as the measurement of the effectiveness of the strategy through the concept of digital value offer.

Hy-Bridge: A Hybrid Blockchain for Privacy-Preserving and Trustful Energy Transactions in Internet-of-Things Platforms.

In the current centralized IoT ecosystems, all financial transactions are routed through IoT platform providers. The security and privacy issues are inevitable with an untrusted or compromised IoT platform provider. To address these issues, we propose Hy-Bridge, a hybrid blockchain-based billing and charging framework. In Hy-Bridge, the IoT platform provider plays no proxy role, and IoT users can securely and efficiently share a credit with other users. The trustful end-to-end functionality of blockchain helps us to provide accountability and reliability features in IoT transactions. Furthermore, with the blockchain-distributed consensus, we provide a credit-sharing feature for IoT users in the energy and utility market. To provide this feature, we introduce a local block framework for service management in the credit-sharing group. To preserve the IoT users’ privacy and avoid any information leakage to the main blockchain, an interconnection position, called bridge, is introduced to isolate IoT users’ peer-to-peer transactions and link the main blockchain to its subnetwork blockchain(s) in a hybrid model. To this end, a k-anonymity protection is performed on the bridge. To evaluate the performance of the introduced hybrid blockchain-based billing and charging, we simulated the energy use case scenario using Hy-Bridge. Our simulation results show that Hy-Bridge could protect user privacy with an acceptable level of information loss and CPU and memory usage.

Simulation in real conditions of navigation and obstacle avoidance with PX4/Gazebo platform

In the future, UAVs should be a part of the IoT ecosystems. Integration of sensors onboard allows to enrich information stored in the cloud and, at the same time, to improve the capacities of UAVs. Developing new sensors and the integration in UAV architecture could improve control functions. Design of future UAV systems requires from advanced tools to analyze the system components and their interaction in real operational conditions. In this work, authors present an approach to integrate and evaluate a LIDAR sensor and the capacity for improving navigation and obstacle avoidance functions in simulated situations using a real UAV platform. It uses available software for mission definition and execution in UAVs based on PixHawk flight controller and peripherals. The proposed solution (a general method that could be used to integrate other kind of sensors) shows physical integration of the main types of sensors in UAV domain both for navigation and collision avoidance, and at the same time the use of powerful simulation models developed with Gazebo. Some illustrative results show the performance of this navigation and obstacle avoidance function using the simulated sensors and the control of the real UAV in realistic conditions.

Blockchain and Trust for Secure, End-User-Based and Decentralized IoT Service Provision

Building trust relationships between different decentralized entities in the IoT ecosystem is essential. Hereof, the combination of blockchain technology and trust evaluation techniques is recently considered as an efficient measure. However, both technologies within the IoT are still facing some limitations which are addressed in this research. First, this publication reviews various blockchain-based trust approaches and depicts their strengths and limitations regarding their usage in decentralized IoT communities. Then, an optimized trust model with a multi-layer adaptive and trust-based weighting system is proposed. Additionally, different trust metric parameters and their mathematical models used for trust evaluation are presented. Moreover, this publication presents a novel approach for incentivization processes in the IoT marketplace using control loops and smart contracts. Thereby, participants are motivated to continuously improve their behavior. Finally, the proposed trust model is proved to be reliable. The experimental results conducted from different scenarios show that the presented approach provides more resiliency against various attacks than existing ones.

SMIoT: a software architecture for maintainable internet-of-things applications

Developing sustainable IoT applications is by far no sinecure. Many IoT apps that are currently on the market can only be coupled with a fixed set of edge devices or technologies. On the contrary, IoT sensors and actuators evolve at a fast pace degrading the attractiveness of many IoT applications over time. The vendor lock-in trap is often triggered by sensor-centric application development. This paper presents application-centric development as an alternative approach to tackle maintainability problems in IoT ecosystems. The paradigm shift is supported by a layered architecture called SMIoT, which guides the design of advanced IoT ecosystems. Applying the architectural principles result in IoT apps that can easily cope with new technologies that come to the market, hence, increasing their lifetime and offering various infrastructural alternatives to end-users. Furthermore, the architectural principles are adopted in an Android framework implementation and validated through the design of a healthcare ecosystem.

Who trusts in the smart city? Transparency, governance, and the Internet of Things

AbstractInternet of Things (IoT) devices such as connected sensors are increasingly being used in the public sector, often deployed and collecting data in public spaces. A theme commonly seen in the rhetoric surrounding public space IoT initiatives is empowerment, and these deployments are broadly perceived as beneficial by policy makers. However, such technology presents new governance challenges. It is important to ask who is empowered and who benefits, and we must ensure that such technological interventions follow democratic principles and are trusted by citizens. In this paper, we investigate how risk, transparency, and data governance require careful consideration in this domain, describing work which investigates how these combine to form components of trusted IoT ecosystems. This includes an overview of the landscape of public space IoT deployments, consideration of how they may often be subsumed in idealized smart city focused rhetoric, and discussion of how methodologies such as design fiction in community settings can uncover potential risks and concerns. Our findings suggest that agency, value and intent associated with IoT systems are key components that must be made transparent, particularly when multiple actors and stakeholders are involved. We suggest that good governance requires consideration of these systems in their entirety, throughout the full planning, implementation, and evaluation process, and in consultation with multiple stakeholders who are impacted, including the public. To achieve this effectively, we argue for transparency at the device and system level, which may require legislative change.

Internet of Things Smart Factories Ecosystem based on SDN

Abstract The smart cities today new a development of a large number of sectors of activities, this make a big Ecosystem that connect a lot of IoT Ecosystems in an interoperable way. In our work we focused on the last generation of Industry, specifically the IoT Smart Factories Ecosystem, that is based on the digitalisation of all the industrial processes, using sensors to collect the information, network technology to send the collected information to the right server in the Internet for decision making, and actuators that react according to need, to make what is called the smart product. To improve the communication inside the IoT Smart Factories Ecosystem, we integrated the Software Define Technology to cam out with a new architecture called the Software Define Internet of Thing Smart Factories Ecosystem.

Fault-resilient and QoS centric dynamic network sensitive routing protocol for mobile-WSNs

The exponential rise in the demand of wireless communication has revitalized academia-industry to achieve more efficient networking solution. To meet these demands wireless sensor networks (WSNs) have always been the dominating solution, however static node and network characteristics confine its suitability for applications under dynamic topology. Strengthening WSN with fault-resilient route decision by exploiting dynamic network parameters such as current congestion probability, buffer availability, and packet injection rate can ensure reliable and quality of service (QoS) communication over WSNs under dynamic network topology. With this motivation, in this paper multiple network parameter-based fault-resilient and QoS centric dynamic network sensitive routing protocol (FQ-DNSRP) is developed. FQ-DNSRP exploits network parameters at the different layers of the IEEE 802.15.4 protocol stack to derive a node rank matrix that helps in identifying best forwarding node for deadline sensitive and reliable data transmission. Simulation results revealed that the proposed FQ-DNSRP model exhibits satisfactory performance for real time data delivery over mobile-WSNs that can be significant for numerous applications, including IoT ecosystems.

Fault-resilient and QoS centric dynamic network sensitive routing protocol for mobile-WSNs

The exponential rise in the demand of wireless communication has revitalized academia-industry to achieve more efficient networking solution. To meet these demands wireless sensor networks (WSNs) have always been the dominating solution, however static node and network characteristics confine its suitability for applications under dynamic topology. Strengthening WSN with fault-resilient route decision by exploiting dynamic network parameters such as current congestion probability, buffer availability, and packet injection rate can ensure reliable and quality of service (QoS) communication over WSNs under dynamic network topology. With this motivation, in this paper multiple network parameter-based fault-resilient and QoS centric dynamic network sensitive routing protocol (FQ-DNSRP) is developed. FQ-DNSRP exploits network parameters at the different layers of the IEEE 802.15.4 protocol stack to derive a node rank matrix that helps in identifying best forwarding node for deadline sensitive and reliable data transmission. Simulation results revealed that the proposed FQ-DNSRP model exhibits satisfactory performance for real time data delivery over mobile-WSNs that can be significant for numerous applications, including IoT ecosystems.

Liberalization of Digital Twins of IoT-Enabled Home Appliances via Blockchains and Absolute Ownership Rights

IoT-enabled home appliances are still in their infancy, especially from the perspective of customers, which hinders widespread market penetration. To relieve this skeptical attitude of customers toward IoT appliances, it is important to design human-centric business models rather than corporate-centric ones. IoT ecosystems that make use of cognitive outputs from the social network of things can assist in the establishment of such business models. The contributions of this article are twofold. First, we propose a reference model that grants the absolute ownership of the fog-located digital twin (DT) of a home appliance to its owner and promotes human-centric services and applications on this twin by utilizing blockchains (BCs) and BC-enabled clouds. Second, by enabling customers to have absolute ownership rights over the fog-located DTs, the model paves the way for the liberalization of DTs as well as the appliances coupled to them, which is an important step in revealing the true value that underlies human-centricity and things-to-things collaboration.

A novel approach to sensor implementation for healthcare systems using internet of things

<p>The Internet of Things is touching all spheres of life, be it in connecting cities together, making agricultural farms and health care smarter, predictable and more secure, and in industries it is set out to bring about changes that are similar to those of the industrial revolution that took place in the 19th and 20th century. It is estimated by pundits that in next 5 to 10 years, the Internet of Things will become a 50 billion dollar industry by itself, encompassing everything that it touches and goes upon. In order to get healthcare enabled into the IoT ecosystem, the sensors and the actuators related to it must be able to support the protocols that is required for the acquisition, processing and storing of data from the sensors to the IoT based infrastructure. Here, for a proposed model for a health care monitor using Internet of Things, the sensors characteristics, working principal, the protocol associated with it, its internal mechanism, and the results obtained when interfaced using a Raspberry Pi are<br />discussed, laying the framework for the future of the sensors that need to be adapted to stay relevant in the future, when IoT transitions from concept to reality.</p>

Updating Competition Policy for the Digital Economy? An Analysis of Recent Reports in Germany, UK, EU, and Australia

All over the world a new critical discussion has emerged about the concentration tendencies in the digital economy and the market power of large digital firms and platforms, like Google, Facebook, Amazon, and others. A particular important question is whether the current competition policies are capable of dealing with these new challenges or whether competition laws have to be amended or complemented by other new policies, e.g. regulatory solutions. This paper analyses four recent extensive reports about this question that were commissioned by the governments of Germany, UK, Australia, and the EU Competition Commissioner Margrethe Vestager (Schweitzer et al report, Furman report, ACCC report, Cremer et al report). In its analysis the paper focuses on the two topics “platforms, large digital firms, market power, and abusive behavior” and “data access/sharing/portability and the specific problems of digital IoT ecosystems”. An important result is that the reports largely agree on the severity of the market power and competition problems, but differ with regard to their main strategies how these problems should be solved.

Word Embeddings for IoT Based on Device Activity Footprints

With the expansion of IoT ecosystem, there is an explosion of the number of devices and sensors and the data generated by these devices. However, the tools available to analyze such data are limited. Word embeddings, widely used in the natural language processing (NLP) domain, provides a way to get similar words to the current word. In this paper, we extend the theory of word embeddings to the area of IoT devices, proposing a method to generate the word embeddings for IoT devices and sensors in a smart home based on their activity. We model IoT devices as vectors using a concept like Word2Vec and App2Vec, where the time between the device firings is also taken into account. These computed word embeddings can be used for a variety of use cases, such as to find similar devices in an IoT device store, or as a signature of each type of IoT device. We show results of a feasibility study on the CASAS dataset and a private real-world dataset of IoT device activity logs, using our method to identify the patterns in embeddings of various types of IoT devices in a household. We get a probability of more than 0.65 for similar types of devices clustering together, independent of session gap value and embedding vector size for the CASAS dataset. We also get a prob-ability of 0.4 on the private dataset, independent of session gap value and embedding vector size.

UNIVERSITIES AS SMART CITY DRIVERS IN SMALL AND MEDIUM-SIZED CITIES

Abstract. Many small and medium-sized cities meet their limitations when it comes to deliver longer running smart city services and to manage the complexity of big data. There is a tendency to be stuck in pilots and smaller set-ups because the knowledge and innovation that is required for these projects and services can’t be obtained in organisations, where there is more focus on daily operations and maintaining service levels in welfare. At the same time there is a need for a scientific baseline in relation to move our urban areas towards a more sustainable future. Someone needs to deliver data that can document the challenges that cities stand up against reaching the UN Sustainable Development Goals (SDG). This paper describes a case where the local university together with a research-based start-up company have taken an initiative to deploy and manage a network of multi-functional probes (MONTEM CityProbes) that contains a large number of sensors that can track a broad suite of environmental data in near real-time. The service is established with open data capabilities and with a hope to kickstart further innovations in smart city developments and to strengthen the IoT eco-system of the region. The specific example focusses on monitoring the air quality from 25 probes deployed in places with strategic importance and where there is heavy traffic intensity from fossil-fuelled motor vehicles.

Data-Sharing in IoT Ecosystems From a Competition Law Perspective: The Example of Connected Cars

This paper analyses whether competition law can help to solve problems of access to data and interoperability in IoT ecosystems, where often one firm has exclusive control of the data produced by a smart device (and of the technical access to this device). Such a gatekeeper position can lead to the elimination of competition for aftermarket and other complementary services in such IoT ecosystems. This problem is analysed both from an economic and a legal perspective, and also generally for IoT ecosystems as well as for the much discussed problems of “access to in-vehicle data and re-sources” in connected cars, where the “extended vehicle” concept of the car manufacturers leads to such positions of exclusive control. The paper analyses, in particular, the competition rules about abusive behavior of dominant firms (Art. 102 TFEU) and of firms with “relative market power” (§ 20(1) GWB) in German competition law. These provisions might offer (if appropriately applied and amended) at least some solutions for these data access problems. Competition law, however, might not be sufficient for dealing with all or most of these problems, i.e. that also additional solutions might be needed (data portability, direct data (access) rights, or sector-specific regulation).

Vulnerability-based risk assessment and mitigation strategies for edge devices in the Internet of Things

Edge computing envisages a distributed decentralized processing of data through a set of edge devices in the proximity of the data origins to improve the network latency and bandwidth usage. However, as the edge devices process important parameters that can often control the performance of the system, they become attractive targets of attackers. In this work, we address the security issues pertaining to the edge devices in the IoT ecosystem because of the existence of vulnerabilities in the network devices. We propose a multi-attacker multi-target graphical model for risk assessment, representing the attackers, targets, and the vulnerability relations in the network. Further, we propose risk mitigation strategies for securing the edge devices.

Forewarned is forearmed

PurposeInternet of Things (IoT) interconnects many heterogeneous devices to each other, collecting and processing large volumes of data for decision making without human intervention. However, the information security concern it brings has attracted quite a lot of attention, and, at this stage, the smart step would be to analyze the security issues of IoT platform and get to the state of readiness before embarking upon this attractive technology. The purpose of this paper is to address these issues.Design/methodology/approachIoT risk assessment through the application of the analytical hierarchy process (AHP), a favorite multi-criteria decision making technique, is proposed. The IoT risks are prioritized and ranked at different layers, before which a well-defined IoT risk taxonomy is defined comprising of 25 risks across six layers of the IoT model for developing control and mitigation plans for information security of IoT.FindingsPeople and processes layer, network layer and applications layer are the top three critical layers with risks like the lack of awareness, malware injection, malicious code injection, denial of service and inefficient policies for IoT practice get the highest priority and rank. Pareto analysis of the overall risk factors revealed that the top ten factors contribute to 80 percent of the risks perceived by information security experts.Research limitations/implicationsThe study focuses only on certain predefined constructs or layers of the IoT model traced from legacy studies. It is essential to re-look these constructs on a timely basis to prolong the results’ validity. The study’s empirical scope is confined only to the risk perception of select IoT experts and does not encompass a broader segment of the IoT ecosystem. Therefore, the risks assessment may not be sweeping to a bigger audience.Practical implicationsThe study implications are two-fold: one it consolidates the earlier siloed works to intensify the need for risk assessment in the IoT domain, and second the study brings yet another contextual avenue of extending the application AHP and Pareto principle combination. The paper also draws specific critical organizational interventions about IoT risks. A comprehensive approach to prioritizing and ranking IoT risks are present in this research paper.Originality/valueThe contribution of this study to the benchmarking of IoT risk assessment is two-fold. One, a comprehensive risk assessment taxonomy is proposed, and two, the risks are prioritized and ranked to give a convincing reference for the organizations while making information security plans for IoT technology.

Internet of Things: Evolution and technologies from a security perspective

In recent years, IoT has developed into many areas of life including smart homes, smart cities, agriculture, offices, and workplaces. Everyday physical items such as lights, locks and industrial machineries can now be part of the IoT ecosystem. IoT has redefined the management of critical and non-critical systems with the aim of making our lives more safe, efficient and comfortable. As a result, IoT technology is having a huge positive impact on our lives. However, in addition to these positives, IoT systems have also attracted negative attention from malicious users who aim to infiltrate weaknesses within IoT systems for their own gain, referred to as cyber security attacks. By creating an introduction to IoT, this paper seeks to highlight IoT cyber security vulnerabilities and mitigation techniques to the reader.The paper is suitable for developers, practitioners, and academics, particularly from fields such as computer networking, information or communication technology or electronics. The paper begins by introducing IoT as the culmination of two hundred years of evolution within communication technologies. Around 2014, IoT reached consumers, early products were mostly small closed IoT networks, followed by large networks such as smart cities, and continuing to evolve into Next Generation Internet; internet systems which incorporate human values. Following this evolutionary introduction, IoT architectures are compared and some of the technologies that are part of each architectural layer are introduced. Security threats within each architectural layer and some mitigation strategies are discussed, finally, the paper concludes with some future developments.

The evolution of the Internet of Things (IoT): A computational text analysis

There is increasing interest in the IoT, in both academia and industry. Extant studies have surveyed the topic of IoT using different approaches. This study takes a digital innovation view of IoT as a complex ecosystem of technologies, industry applications, concepts, methodologies, and social institutions, which is temporally dynamic and evolves over time. The study focuses on three research questions: (1) What are the important elements of the IoT ecosystem? (2) How are such IoT elements connected in the ecosystem? And (3) How have such IoT elements been evolving over time? This study adopts a topic modeling approach and extracts hidden trends from social media data. The popular elements in the IoT ecosystem are cloud computing, big data, and cybersecurity, among others. The analysis provides detailed information about popular categories or topics in the IoT ecosystem, the associations among those topics, and their evolution since 2014. Based on the findings, the study offers implications for practice and suggestions for future research.

Address Space Layout Randomization Next Generation

Systems that are built using low-power computationally-weak devices, which force developers to favor performance over security; which jointly with its high connectivity, continuous and autonomous operation makes those devices specially appealing to attackers. ASLR (Address Space Layout Randomization) is one of the most effective mitigation techniques against remote code execution attacks, but when it is implemented in a practical system its effectiveness is jeopardized by multiple constraints: the size of the virtual memory space, the potential fragmentation problems, compatibility limitations, etc. As a result, most ASLR implementations (specially in 32-bits) fail to provide the necessary protection. In this paper we propose a taxonomy of all ASLR elements, which categorizes the entropy in three dimensions: (1) how, (2) when and (3) what; and includes novel forms of entropy. Based on this taxonomy we have created, ASLRA, an advanced statistical analysis tool to assess the effectiveness of any ASLR implementation. Our analysis show that all ASLR implementations suffer from several weaknesses, 32-bit systems provide a poor ASLR, and OS X has a broken ASLR in both 32- and 64-bit systems. This is jeopardizing not only servers and end users devices as smartphones but also the whole IoT ecosystem. To overcome all these issues, we present ASLR-NG, a novel ASLR that provides the maximum possible absolute entropy and removes all correlation attacks making ASLR-NG the best solution for both 32- and 64-bit systems. We implemented ASLR-NG in the Linux kernel 4.15. The comparative evaluation shows that ASLR-NG overcomes PaX, Linux and OS X implementations, providing strong protection to prevent attackers from abusing weak ASLRs.