Privacy-preserving Secure Media Streaming for Multi-user Smart Environments

Iod-Nets – An IoT based intelligent health care monitoring system for ambulatory pregnant mothers and fetuses

Visual privacy protection methods: A survey

Wearable monitoring, which has the advantages of continuous monitoring for a long time with low physiological and psychological load, represents a future development direction of monitoring technology. Based on wearable physiological monitoring technology, combined with Internet of Things (IoT) and artificial intelligence technology, this paper has developed an intelligent monitoring system, including wearable hardware, ward Internet of Things platform, continuous physiological data analysis algorithm and software. We explored the clinical value of continuous physiological data using this system through a lot of clinical practices. And four value points were given, namely, real-time monitoring, disease assessment, prediction and early warning, and rehabilitation training. Depending on the real clinical environment, we explored the mode of applying wearable technology in general ward monitoring, cardiopulmonary rehabilitation, and integrated monitoring inside and outside the hospital. The research results show that this monitoring system can be effectively used for monitoring of patients in hospital, evaluation and training of patients' cardiopulmonary function, and management of patients outside hospital.

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...

Virtual sensors promise numerous benefits to the Internet of Things (IoT) in terms of enhanced computing on sensor data, sensor fusion and overall cost reduction. But a wide deployment of this concept in the IoT system is not witnessed due to a lack of uniform approach to create and maintain them. Also, virtual actuators are not fully explored yet. This paper proposes a uniform mechanism to create and operate a virtual IoT device (VID) that can represent either a virtual sensor or a virtual actuator. VID integration into an IoT architecture is presented and operational phases are explained. Utilization of the virtual IoT devices in an horizon IoT application involving connected vehicles and Smart City is outlined. The main novel aspects of the work are - (i) remote creation of VID by a system administrator and/or a consumer, (ii) standard web technology based implementation of VID promoting interoperability in IoT architecture, (iii) generic and flexible deployment, (iv) support of discovery and management of VIDs through the IoT architecture and (v) ability to communicate to both smart and legacy IoT devices.

Under the pressures of global market uncertainty and rapid production changes, the labor-intensive industries demand instant manufacturing site information and accurate production forecasting. This research applies sensor modules with noise reduction, information abstracting, and wireless transmission functions to form a flexible internet of things (IoT) architecture for acquiring field information. Moreover, AI models are used to reveal human activities and predict the output of a group of workstations. The IoT architecture has been implemented in the actual shoe making site. Although there is a 5% missing data issue due to network transmission, neural network models can successfully convert the IoT data to machine utilization. By analyzing the field data, the actual collaboration among the worker team can be revealed. Furthermore, a sequential AI model is applied to learn to capture the characteristics of the team working. This AI model only requires training by 15 min of IoT data, then it can predict the current and next few days’ productions within 10% error. This research confirms that implementing the IoT architecture and applying the AI model enables instant manufacturing monitoring of labor-intensive manufacturing sites and accurate production forecasting.

Internet of things (IoT) has become one of the most prominent technologies that the world has been witnessing nowadays. It provides great solutions to humanity in many significant fields of life. IoT refers to a collection of sensors or object in the universe with the capability of communicating with each other through the internet without human intervention. Currently, there is no standard IoT architecture. As it is in its infancy, IoT is surrounded by numerous security and privacy concerns. Thus, to avoid such concerns that may hinder its deployment, an IoT architecture has to be carefully designed to incorporate security and privacy solutions. In this paper, a systematic literature review was conducted to trace the evolvement of IoT architectures from its initial development in 2008 until 2018. The Comparison among these architectures is based on terms of the architectural stack, covered issues, the technology used and considerations of security and privacy aspects. The findings of the review show that the initial IoT architectures did not provide a comprehensive meaning for IoT that describe its nature, whereas the recent IoT architectures convey a comprehensive meaning of IoT, starting from data collection, followed by data transmission and processing, and ending with data dissemination. Moreover, the findings reveal that IoT architecture has evolved gradually across the years, through improving architecture stack with new solutions to mitigate IoT challenges such as scalability, interoperability, extensibility, management, etc. with lack consideration of security solutions. The findings disclose that none of the discussed IoT architectures considers privacy concerns, which indeed considered as a critical factor of IoT sustainability and success. Therefore, there is an inevitable need to consider security and privacy solutions when designing IoT architecture.

The subject of the article is the presentation of building the model of the Internet of Things (IoT) architecture in environmental engineering. The starting point is the existing four-stage IoT architecture models. The article suggests adding the fifth stage - managing the IoT system construction process, including the creation of three additional layers. The approach proposed in this article was verified in the construction of the air quality assessment system in Gdansk in which the system architecture integrates the management stage. The developed model is the basis for the ontological model of IoT architecture developed by the authors and presented in this article, easy to implement in the construction of system architectures in environmental engineering.

Layered internet of things (IoT) architectures have been proposed over the last years as they facilitate understanding the roles of different networking, hardware, and software components of smart applications. These are inherently distributed, spanning from devices installed in the field up to a cloud datacenter and further to a user smartphone, passing by intermediary stages at different levels of fog computing infrastructure. However, IoT architectures provide almost no hints on where components should be deployed. IoT Software Platforms derived from the layered architectures are expected to adapt to scenarios with different characteristics, requirements, and constraints from stakeholders and applications. In such a complex environment, a one-size-fits-all approach does not adapt well to varying demands and may hinder the adoption of IoT Smart Applications. In this paper, we propose a 5-layer IoT Architecture and a 5-stage IoT Computing Continuum, as well as provide insights on the mapping of software components of the former into physical locations of the latter. Also, we conduct a performance analysis study with six configurations where components are deployed into different stages. Our results show that different deployment configurations of layered components into staged locations generate bottlenecks that affect system performance and scalability. Based on that, policies for static deployment and dynamic migration of layered components into staged locations can be identified.

Nowadays, IoT devices are found everywhere such as schools, universities, malls, and hospitals to perform beneficial functionality. The Internet of things (IoT) is a set of devices that contain electronics, software, sensors, actuators, and connectivity that enable the connection and transmit data. There are many applications of IoT in different fields such as smart home, smart health, smart mobility, and smart grids. Smart Grid is the modern power system, which is a development and integrates the power grids with Information and Communication Technology (ICT) to ensure reliable and safe power delivery to the customers. IoT has developed as one of the technologies that make a smart grid network to be possible. Moreover, there are many security risks and issues that have been raised in the field IoT which can impact the security and privacy of users. Due to this, security became a serious factor we must pay attention to implement the IoT based smart grid networks. Due to the limitations of IoT devices such as computing power, and the powerful of IoT devices, the IoT systems are susceptible to the cyber-attacks that can impact the security and privacy of IoT networks and users. In this paper, we will present the security protocols for IoT, the architecture of IoT, and the cyber-threat in the IoT. As well as, the limitations of IoT devices, security issues and risks that affect the privacy of data exchanged between the Internet of Things (IoT) devices especially in smart grids. Also, the security mechanisms and measures to ensure the security and the user's privacy on the IoT ecosystem and smart grids.

In response to the deformation and displacement problems that exist during the construction and use of underground projects, this study develops an underground engineering robot measurement deformation monitoring system based on the Internet of Things (IoT) architecture, aiming to improve the accuracy and efficiency of underground engineering deformation monitoring. The system was designed with a multi-layer architecture, including a perception layer (real-time collection of deformation data) and a network layer (using a robot to carry a data acquisition terminal and transmit data to a cloud server through wireless communication technology), platform layer (using cloud computing and big data technology to store, process, and analyze collected data), and application layer (visualization platform, convenient operation, and analysis of data). Fifteen underground engineering projects were tested, with ten key monitoring points selected for each project. Multiple regression analysis was used to evaluate the monitoring accuracy and stability and to explore the relationship between monitoring data and geological conditions and environmental variables. The experimental results show that compared with traditional methods, this system has significant advantages in stress monitoring: the stress monitoring error of conventional methods is about 0.5 MPa, while the error of this system is only 0.01 MPa, a difference of 50 times. The system of the IoT significantly improved the detection efficiency compared with the traditional manual surveying and mapping method, and the underground engineering robot measurement deformation monitoring system based on the IoT architecture took only 4 h to monitor the small deformation. However, the traditional method took 15 h, i.e., the system based on the IoT was 11 h faster than the conventional method. The underground engineering robot measurement deformation monitoring system based on the IoT architecture has high reliability and operability, and provides strong support for the safety management of underground engineering.

With the development of Internet of Things (IoT), wearable devices have gradually become popular, and different new network architectures have also been proposed. Social Internet of Things (SIoT) is a newly proposed architecture that allows devices to realize social-like self-selection and connection. This project is aimed at wearable devices, and uses the Erdös-Rényi (ER) random model and general random number generation methods to simulate the topology based on the IoT architecture and the SIoT architecture, and analyze the closeness centrality and degree centrality of the nodes in the topology and the overall. Finally, it is found that the topology based on the SIoT architecture is better than the topology based on the IoT architecture in terms of node and overall network expansion. This project can provide a certain reference for future distributed IoT network research.

With advent of smart cities, the IoT infrastructure is expanding in an exponential manner. This emerging infrastructure is going to produce a huge amount of data to be processed. Besides the data processing bottleneck, energy efficiency, security, interoperability and scalability of the network standard poses another problem to the present Internet of Things (IoT) architecture. So this become an interesting research issue which aims to improve the present IoT architecture by incorporating Software Defined Network (SDN) system in it. SDN, a relatively new paradigm has the capability of resolving the mentioned complexities. If SDN can be incorporated in traditional IoT architecture this will help to resolve many IoT problems. Now the research issue becomes as how to design an effective protocol which can bridge between the traditional IoT and SDN system for effective interoperability. In SDN, control operation are designated in the middle-ware layer, where SDN controllers are placed. Controllers maintains the operation of the whole network. In this paper, an investigation has been made to design a protocol, termed as 6LoWSD protocol, which has the ability to integrate the two systems. Required experimentation have been carried out on simulation to ascertain the effectiveness of the proposed protocol. Here, 6LoWSD was simulated on Contiki platform. 6LoWPAN has been used for the IoT system and OpenFlow for the SDN system. The experimental results displayed quite satisfactory outcomes.

This article analyzes and highlights the security perspective of Internet of Things (IoT) connected devices and their communication challenges, as IoT is considered one of the key emerging fields in Industry 4.0. The IoT architectures can consist of physical systems, virtual ones or even hybrids, combining a collection of different physically active things, sensors, cloud services, specific IoT protocols, communication layers, users and developers. On top of all, it is the business layer, because the scope of the entire IoT environment is to deliver data, to monitor and to facilitate the management of complex processes. In order to facilitate the data exchange between the IoT layers, there have been developed a series of protocols particular to the IoT domain. As in many IT related fields, the solutions are not perfect from the data security and privacy perspectives, many challenges being still open research issues. As the two concepts of IoT and Cloud of Things are connected, bringing real world data into the Cloud to process it, raises Cloud Computing security concerns regarding the privacy and security of data. Although in recent years, many efforts have been made to improve Cloud Computing security, there are risks that need to be taken into consideration. From the Web of Data’s point of view, things are even more prone to security risks. Because privacy is one of the fundamental right of digital users, it is extremely important for new technologies to comply with privacy regulations and policies, such as the new European data protection and privacy frameworks. In this context, companies must take into account standards, challenges and new trends in IoT. In the absence of specific measures, raw or processed data can be easily stolen from the Web of Data. In this paper we analyze and present the main protocols of communication in the IoT field from a data security perspective. Also, we do a review of the main architectures that can improve the security of the communication between IoT devices and the Cloud data storage.

PurposeThe technology used by an organization is significantly influenced by the organization’s preferred competitive capabilities. The Internet of things (IoT) is an important technology, which is implemented by most prominent business organizations. The purpose of this paper is to investigate the relationship between an organization’s strategies and the IoT architectures implemented by the organization.Design/methodology/approachThis study has been carried out on primary data collected with the help of a structured questionnaire. The data have been analyzed by statistical techniques like cluster analysis and discriminant analysis through SPSS.FindingsThe empirical investigation of data revealed that there is a relationship between organizational strategy and IoT architectures. The three-layered architecture of the IoT is most suitable for caretakers; the three-, four- or five- layered architectures are suitable for marketeers; whereas innovators find it more suitable to use five- or more-layered architecture of the IoT. This paper draws the conclusion based on maximum likelihood rather than using statistical analyses like ANOVA. The idea behind using the maximum likelihood estimate is that there are many subjective parameters in deciding the architectures of the IoT. These subjective parameters are difficult to quantify, so it is not possible to apply ANOVA on these parameters.Research limitations/implicationsThis study considers three organizational strategies; the relationship between other organizational strategies and IoT architecture will be studied in future.Practical implicationsThis study offers multiple opportunities to practitioners and consulting firms of the IoT to adopt a suitable IoT architecture according to the organizational strategy. This study equips IoT development engineers to select suitable technology for data capturing, data transmission, and data management and access for an IoT architecture.Originality/valueAlthough a lot of work has already been done on the architecture of IoT for different industries and businesses, to the best of our knowledge, this is the first study that relates organizational strategies to IoT architectures. This study applies to all the major industry types.