Future Access Enablers for Ubiquitous and Intelligent Infrastructures

Given the considerable amount of data (including sensitive and personal information) collected, stored, disseminated by mobile devices, there is a need to ensure that such devices can be securely wiped when they are misplaced, stolen or disposed. Hence, in this paper we evaluate the effectiveness of three categories of wiping applications: Factory Reset, Remote Reset, Data Wiping Applications (apps). Specifically, we study two popular wiping apps (i.e., Shreddit – Data Eraser by PalmTronix, and Secure Wipe by Pinellas CodeWorks) and install both apps on three test devices, namely: Samsung S5 (Android 6.0.1), Samsung S5 Active (OS version 6.0.1), and an iPhone 6S (iOS 13.2.2). We then study the extent of data that can be recovered, from the three categories of wiping, using two popular commercial mobile forensic software, namely: Mobile Phone Examiner Plus (MPE+) from Accessdata, and MOBILedit from Compelson labs.

LoRa technology provides low power, long range and low data rate communication solution for sensor nodes on Internet of the Things (IoT) applications. In this work, we study experimentally the performance of LoRa radio for a device-to-device communication with different spreading factors. A measurement campaign is carried out under different scenarios such as outdoor, indoor, different altitudes, and different distances. In all scenarios, we measure Packet Delivery Ratio (PDR) and Signal to Noise Ratio (SNR). The results show that the distance between a transmitter and a receiver is not the only effective parameter determining the SNR but also environmental conditions and the altitude of a receiver impact on the SNR. We show also that the PDR depends on the applied spreading factor. Besides, we derive a mapping between the SNR to a proper spreading factor of the LoRa radio for different PDR requirements using our empirical results. Applying this mapping, we propose a self-organized algorithm that adapts the spreading factor in LoRa radio to achieve a required PDR. The results show that the proposed adaptive scheme adapts the LoRa radio to provide a given 80% PDR requirement between two LoRa nodes.

Nanonetwork has given rise to many other disciplines like agriculture, defense, health care, and industrial applications. With nanonetwork there exist tiny nanodevices or nanomachines. The interconnection of tiny nanodevices with internet helps to make an entire network i.e. the next generation of network, named nanonetwork. Nanodevices, due to their small sizes, have several limitations like communication range, frequency range, energy consumption rate, limited amount of memory and many others. Developing protocols and routing framework is quite a challenging task for nanonetworks. This research work will explore the scarce availability of energy in nanonetworks by digging in the existing routing protocols, especially on the ones designed to cater the energy constraint. The opportunities and challenges of existing work will be investigated and discussed. Furthermore, a solution will be devised and its effectiveness will be stated that will pave its way in the future activities of energy efficient nanorouting protocols.

Wireless network (radio) virtualization and its synergy with ML/AI-based technologies is a novel concept that can efficiently address problems of legacy networks, such as flash crowds. This paper discusses the integration aspects of intelligence-based technologies with Sate-of-the-Art end-to-end reconfigurable, flexible and scalable network architecture, capable of handling demands in flash crowd scenarios. The presented results, demonstrate that advanced solutions based on ML can significantly improve the network proactivity and adaptivity by reliably predicting flash crowd scenarios. The results also show that in case of low dataset fidelity, conventional statistical models are a more suitable option.

The initial signaling and data exchanges over open wireless transmission channels in vehicular ad hoc networks (VANETs) renders these networks susceptible to security and privacy violation attacks such as impersonation and packet replays. To curb this, a number of protocols have been proposed such as Public Key Infrastructure (PKI) based schemes, identity (ID) based schemes, anonymity based approaches and password or biometric based schemes. However, PKI based schemes have high computational overheads while ID based schemes are vulnerable to denial of service attacks (DoS). On the other hand, password and biometric based schemes employ the long term shared secrets stored in tamper proof devices (TPD) as the sole authentication factor, rendering them vulnerable to side-channel attacks. On their part, anonymity based approaches employ either digital certificates, pseudonyms or group signatures. However, these schemes do not offer trajectory privacy, conventional signature signing and verification is inefficient, and certificate storage or revocation leads to high storage and computation costs. In this paper, a multi-factor mutual authentication protocol that addressed some of these attacks is proposed. This scheme eliminates the requirement for long term storage of secret keys on TPD and remained secure even in the face of on-broad unit (OBU) active physical attack. Simulation results showed that the proposed protocol is robust against attacks such as privileged insider, masquerade and packet replay. It also preserved backward key secrecy, forward key secrecy, password secrecy and anonymity. Its performance evaluation revealed that it exhibited average computation and communication overheads, in addition to average beacon generation and verification latencies.

MPLS and SD-WAN are technologies which ensure the quality of service in a different way. MPLS is a network technology which, with its method of routing the network packets, ensures the end-to-end service to users. On the other hand, SD-WAN ensures the global overview of the entire network and central managing thus enabling easy configuration or exchange of the already existing configuration system. The topic of this paper is analysis of these two network technologies by having them configured and simulated in the software tool GNS3. After that the analysis of the traffic network has been carried out. Regarding the ever-increasing development of the network technologies, an overview of the SD-WAN technology has been provided, as the new paradigm and its potential future applications.

An intrusion detection system (IDS) is an essential component of computer networks to detect and secure the system and environment from malicious activities and anomalous attacks. The convolutional neural network (CNN) is a popular deep learning algorithm that has been broadly applied in the field of computer vision. More recently, several researchers attempted to apply CNN for IDSs. However, the majority of these ignore the influence of the overfitting problem with the implementation of deep learning algorithms, which can impact the robustness of CNN-based anomaly detection systems. In this paper, we investigate the use of CNN for IDSs and propose a technique to enhance its performance by using two popular regularization techniques to address the overfitting problem. Our technique improves the capability of IDSs in detection of unseen intrusion events. We use InSDN benchmark dataset to train and evaluate the performance of our technique. The experimental results demonstrate that the regularization methods can improve the performance of CNN-based anomaly detection models for the software-defined networking (SDN) environment.

The installation of new network devices in the production environment represents a process of several steps. First of all, it is necessary to connect the hardware and then define all the necessary global and local parameters by using the Command Line Interface (CLI) and so for each device in the implementation separately. With the development of automation models within the concept of Software Defined Networks (SDN), the Zero Touch Provisioning (ZTP) occurs as a potential solution to reduce the complexity of installation of a new network infrastructure. The ZTP model can be used to reduce time and costs of installing new devices in the network. This paper presents a case study of implementing the ZTP model on the example of Cisco CSR1000v network device in the local area network. The initial step was the creation of the network environment in the emulation software Emulated Virtual Environment Next Generation. In the network environment the necessary servers were defined and the device that supports the ZTP model was assigned. Then it was necessary to create a script in the Python programming language and upload it to the appropriate server. At startup the device downloads the script from the server. The script is then executed, and as the result of this process, the appropriate configuration on the device is applied. After the implementation of the ZTP model and review of the results, the potential that enables such a solution in networks of much larger scales is evident. The application of this model would certainly simplify the process of installing new devices on the network. The applied ZTP model and the created one’s own script have proven significant saving in the installation time (over 95%), at the same time achieving also a saving in the costs of employees, and affecting a reduction in human error. The results of this paper can contribute to better understanding of the process of implementing the ZTP model with the aim of its more widespread application.

Recently, Social Network Analysis studies have led to an improvement and to a generalization of existing tools to networks with multiple subsystems and layers of connectivity. These kind of networks are usually called multilayer networks. Multilayer networks in which each layer shares at least one node with some other layer in the network are called multiplex networks. Being a multiplex network does not require all nodes to exist on every layer. In this paper, we built a criminal multiplex network which concerns an anti-mafia operation called “Montagna” and it is based on the examination of a pre-trial detention order issued on March 14, 2007 by the judge for preliminary investigations of the Court of Messina (Sicily). “Montagna” focus on two Mafia families called “Mistretta” and “Batanesi” who infiltrated several economic activities including the public works in the north-eastern part of Sicily, through a cartel of entrepreneurs close to the Sicilian Mafia. Originally we derived two single-layer networks, the former capturing meetings between suspected individuals and the latter recording phone calls. But some networked systems can be better modeled by multilayer structures where the individual nodes develop relationships in multiple layers. For this reason we built a two-layer network from the single-layer ones. These two layers share 47 nodes. We followed three different approaches to measure the importance of nodes in multilayer networks using degree as descriptor. Our analysis can aid in the identification of key players in criminal networks.

The current most established IoT platform assessment standard called CREATE-IoT is missing essential KPIs that cover both technical and business aspects. These new KPIs would enhance this standard and improve the quality of assessment outcomes, which eventually would encourage more IoT platform deployments worldwide and open more technology-related jobs that will drive the global economy upward. Through experiences in studying IoT platform technical architecture and business model, this paper formulates and adds 22 unique new KPIs to this standard that initially consists of 198 KPIs. Or conclusively, 11.11% of distinct enhancement has been made. Thus, now this enhanced version of CREATE-IoT assessment standard may cover more IoT platform elements than before.

Internet of things has been a part of our lives, both at home and in workplace, for several years now. However, due to its popularity, numerous security issues are emerging related to devices, network communication or Internet of things (IoT) acquired data storage and processing in the cloud. This paper presents a model for categorization of existing and novel IoT services based on estimated security risks. The goal is to develop security requirements for each service category in such a way that service creators are able to classify their services and follow the requirements in order to harden the services in development. The paper proposes a categorization model based on DREAD (Damage potential, Reproducibility, Exploitability, affected users, and Discoverability) and gives examples of existing services classification. A set of simple questions is proposed at the end of the paper that should be answered by service creators in order to categorize its service into one of the proposed categories.

The concept of the Internet of Things (IoT) is a widely applicable set of technologies and services. Therefore, it is essential to have a clear insight into the trends of development and application of this concept in different vertical and horizontal economic areas and follow future trends’ predictions. In this way, it is possible to direct future research into several problems in those areas where the concept of IoT is most widespread. With this research, the analysis is focused on the smart home environment as one of the most common and fastest-growing applications of the IoT concept. The positive trends of current and future growth of this area in various categories and functionalities of IoT devices such as comfort and lighting, energy, security, monitoring, entertaining and home appliances have been confirmed. Growth is seen in the number of devices used, the number of homes using at least one IoT device, total revenue and market value. Therefore, it is concluded that it is necessary to intensify efforts in researching problems related to smart homes by optimizing access communication networks, the impact of generated traffic on core network parameters, cybersecurity, identification and classification of such devices in the network, development of innovative smart services home and several other research challenges.

The paper describes design of smart production system with full digitalization for requirements of Industry 4.0. The system consists of three level of technologies: production technologies, inspection subsystem and digitalization software system. Production technologies creates parts for assembly: small CNC, Rapid prototyping device and standardized parts storage with assisted assembly process by collaborative robot combined with mixed reality device. This system provides assisted assembly work cell. Inspection subsystems consist of RFID readers with passive tags, vision system with basic 3D inspection, multi-spectrum light for error detection and 3D profilometer precise measuring. Digitalization software is represented as Digital Twin model implemented to server, which uses OPC communication for data transfer from production system to Cloud Platform with additional data from IoT devices.

Industry 4.0 is an application of the network concept of digital objects interconnection and the collection, exchange, analysis and distribution of data among them in industrial enterprises. For this purpose, other technologies belonging to the Industry 4.0 concept are also used. By appropriate application of these technologies, companies can obtain relevant information about the ongoing level of quality of the production process. Improving quality will significantly increase the profitability of the product and will act as a key strategic factor in the market. Many manufacturing companies use traditional manual techniques to assess product quality control. They take a sample from one batch at random and check the quality of the product at different points on the line. However, such an approach has its limitations and does not allow active intervention in the production process. A possible solution is to use the Internet of Things approach, which allows manufacturers to analyse product data that is generated from devices and thus they are informed about the quality of the production process in real time. Product data can be further used to remotely diagnose of the product and reduce the time it takes to process customer service requests.It this paper will be described some technologies, which can help to achieve these aims and there will be also designed a possible information flow to get appropriate data.

The Industry 4.0 concept represents a new way of managing production processes. With its application, connections between people, systems, and objects become more complex, creating a dynamic and real-time optimized network. With the establishment of such a network, a smart factory is created. In a smart factory environment, each process must be precisely planned into a connected functional unit in order for the production process to run smoothly. A factory designed in this way has a complex information and communication infrastructure, and thus potentially more significant security threats and risks that it faces than a factory that operates traditionally. The technologies found in the smart factory environment have been evolving for some time. However, their integration with industrial systems poses new security challenges. The smart factory environment's rapid development imposes the need to ensure safe interaction between the production system elements. This paper provides an insight into the environment of a smart factory and the information and communication technologies that enable its operation. The paper provides an overview of security threats and risks that such an environment faces based on the acquired knowledge.

With the application of a new generation of information technology in the field of manufacturing and the deep integration of computer technology and manufacturing, industrial production is moving towards intellectualization and networking . Because the current production system cannot fully exploit the value of industrial data and the existence of information islands in the production process, this paper presents a study on the development, testing, and evaluation of a machine learning process that can be run on low-cost standard microcontrollers with limited computing and memory resources. This paper first analyzes the basic idea of whether it is possible to develop software for intelligent sensors whose algorithms run on microcontrollers. At the same time, it is considered whether the training and the adaptation of the model parameters can be done on the microcontroller to enable an online adaptation of the machine to be monitored. The goal is a closed system that does not need a backend and the storage of large amounts of data is not necessary.

The focus of this paper is to find out the impact made by aircraft on the environment of Europe. In this paper, we will focus on how far aircraft are influencing and contaminating the environment. The paper cover-up the various case studies conducted by different authors to estimate the impact by various universal indicators and to ascertain the level of the impact made by the particular factors on the environment and comparing the EU facts and figures with that of policies put forward by the various governments which are U.S and Australia. Paper evaluates the facts and figures to identify the ascertain the environmental hazards caused by aircraft across the globe. The aviation industry is presently responsible for 12% of worldwide CO2 dis-charges. Aviation could represent up to 24% of worldwide outflows by 2050 except if there is a critical innovative move. Surveys hydrogen's potential as a greener method of impetus and talks about the significant difficulties for its appropriation.Some studies find several broad ways in which the aviation industry’s emissions could be decreased. The main advantage of using hydrogen technology is zero emissions. In addition, the hydrogen needed for operation is generated from renewable sources. Another advantageous hydrogen fuel cell vehicle and the growing interest is that it has comparable properties to conventional vehicles.

Unmanned Aerial Vehicles (UAVs), or drones, are used in the field of remote collection of images at the time of flight. They can also detect irregularities in vehicle parking and issue fines in case of parking violations. The parking monitoring system uses real-time visual information. In this paper, the proposed solution is for real-time monitoring of areas and detecting irregularities in-vehicle parking using a fleet of drones. In this study, a camera mounted on UAVs applies for taking pictures of public areas at predetermined points. For monitoring of area will be used Observer UAVs while for detection will be used, Inspector UAVs. Visual information collected with UAVs is used to detect irregularities in vehicle parking, while the processing of collected data is performed by an artificial neural network.

Significant progress has been made in the field of deep learning through intensive research over the last decade. So-called convolutional neural networks are an essential component of this research. In this type of neural network, the mathematical convolution operator is used to extract characteristics or anomalies. The purpose of this work is to investigate the extent to which it is possible in certain initial settings to input aerial recordings and flight data of Unmanned Aerial Vehicles (UAVs) in the architecture of a neural network and to detect and map an object. Using the calculated contours or dimensions of the so-called bounding boxes, the position of the objects can be determined relative to the current UAV location.

HŽ Infrastructure Ltd is a company in charge of management, maintenance, and building of railway infrastructure which is obliged to provide the user with all relevant information on the departure and arrival of trains and possible delays. There are currently 545 official places (stops and stations) on the Republic of Croatia’s railway network. To implementing modern communication solutions in the function of informing passengers, it is essential to make a systematic analysis of the technical-technological ecosystem to connect all the elements and deliver information to passengers. In this paper, an analysis of the current state of telecommunication infrastructure and equipment of all official places on the Republic of Croatia’s railway network is made. Based on the analyzed data, the central system’s functions, the passenger information system’s conceptual architecture, and the way the system communicates with the vehicle are defined. The technical-technological requirements that end users must obtain accurate and real-time information can be implemented according to the phased introduction and upgrade of the system, which is visible in the passenger information system’s proposed conceptual architecture in this paper.

The applicability of characteristics of local magnetic fields for more precise determination of localization of subjects and/or objects in indoor environments, such as railway stations, airports, exhibition halls, showrooms, or shopping centers, is considered. An investigation has been carried out to find out whether and how low-cost magnetic field sensors and mobile robot platforms can be used to create maps that improve the accuracy and robustness of later navigation with smartphones or other devices.

In 2020, we investigated the quality of online meetings to find out whether various video and audio degradations can affect end-users’ perception and experience. We collected a total of 542 questionnaires that were suitable for analysis. This paper uses the results to compare the Quality of Experience for three popular videoconferencing applications: Skype, Microsoft Teams, and Zoom. Due to the COVID-19 (Coronavirus disease 2019) and anti-epidemic measures, survey participants were all faced with using these applications daily, whether for work, attending lectures, or keeping in touch with friends and family. They rated their frustration level for specific quality degradations (e.g., blocking of the image or echo in the audio). The paper shows how the three applications compare to each other when different network performance degradation situations occur and how they affect the end user’s perception.

As smartphones and smartphone applications are widely used in a healthcare context (e.g., remote healthcare), these devices and applications may need to comply with the Health Insurance Portability and Accountability Act (HIPAA) of 1996. In other words, adequate safeguards to protect the user’s sensitive information (e.g., personally identifiable information and/or medical history) are required to be enforced on such devices and applications. In this study, we forensically focus on the potential of recovering residual data from Android medical applications, with the objective of providing an initial risk assessment of such applications. Our findings (e.g., documentation of the artifacts) also contribute to a better understanding of the types and location of evidential artifacts that can, potentially, be recovered from these applications in a digital forensic investigation.

Environmental air quality often affects human health. Allergens, viruses, bacteria often float in the air and settle on surfaces. This situation prompts various world organizations to address this problem by means of disinfection and cleaning of premises where a person is most often. Pathogenic bacteria are often spread by airborne droplets and can persist on surfaces for a long time. The proposed study was aimed at proposing a device for a disinfecting room without harm to human health. The multifunctional SMART cleaner is based on the existing and proven properties of UV light to ensure disinfection of not only air but also surfaces. The multifunctionality of the device is represented by different modes of operation and functionality, and the intelligent control unit provides wireless communication with the detection sensor and adjustment of operating modes and cleaning intensity. The properties and parameters of individual components of the device, as well as market research made it possible to assert that the device is effective and also meets modern requirements.

Success in the market in today's highly competitive environment is influenced not only by the quality of products and services of a given enterprise or individual but also by the way they are promoted in the marketing sphere. Enterprises are looking for a variety of promotions, from ordinary flyers in mailboxes to large, expensive advertisements on TV screens. To attract the attention of potential customers, enterprises are forced to continually invent new ways of promotion. Advanced technology is available on the market, which almost every potential customer always has with them. Mobile marketing is now widely used, especially in the form of advertising on the Internet or in most freely available applications. The priority of the article is to increase the competitiveness of the enterprise through augmented reality. By using these technologies, the brand is presented to customers as advanced, which automatically improves its reputation in the market.

We are currently witnessing an increasing demand for residential, office or multifunctional buildings . Customer requirements are no focused only on the economic parameters of the construction, but also on the parameters related to the sustainability and environmental aspect of the construction. In addition, sustainable constructions can be supported by the latest smart technologies. An application of the sustainable approach to constructions is demonstrated by environmental assessment systems.A brief analysis of knowledge in the field of construction sustainability and smart technologies supporting especially the ecological aspect of sustainability is prepared. These findings represent the theoretical basis for comparing the sustainability of construction on selected construction projects. The aim of the paper is to point out the use of ecological smart technologies that affect the sustainability of buildings. The research was carried out on selected sustainable buildings in Europe which received an outstanding rating within the environmental assessment of buildings by significant certification systems.

The article deals with the utilization of renewable energy sources in the construction and maintenance of transport infrastructure. In the introduction of the article, the authors present a brief introduction to this issue. The authors present a system that utilizes renewable energy sources, specifically solar energy, called the Solar Road System. The article describes the functionality of this system and selected advantages and disadvantages over conventional methods of winter road maintenance. In the third chapter, the authors point out the possible use of the solar road system in the wider scope of transport infrastructures, specifically the chapter focuses on the possibilities of using the system in airport construction, where the authors show this principle using a conceptual model of the airport. This chapter briefly describes the winter maintenance of airport operating areas. At the end of the article, the authors point out the possible directions that the development in this area will take and the issues that will need to be addressed in the future.

Smart technologies and solutions have represented an increasing growth in every industry over the last decade . Many of the smart solutions are focused on improvement with a view to sustainability. The basis of smart solutions is advanced technologies and interactive systems that respond to changed conditions. These technologies are increasingly being implemented in the field of construction and intelligent buildings or urban areas. The construction industry shows great possibilities for the implementation of smart and progressive technologies. However, construction projects represent a volume-intensive investment. The same applies to the implementation of smart solutions, which, however, can also provide savings. This needs to be evaluated very much. It is necessary to use evaluation methods of investments in these solutions. This paper is largely devoted to the evaluation methods of investments in mobile applications and smart technology in the construction industry. The research aims to conduct an overview of evaluation methods of investments to smart technology in construction projects. Research also describes examples of the use of specific smart solutions in the construction industry and urban planning. The output of the research is an overview of Evaluation methods of investments, which can be applied and used in assessing investments in advanced technologies in construction.

The article introduces a robust stability and robust performance investigation of two embedded systems for control of electrohydraulic power steering in mobile machinery . They are based on advanced control techniques - linear-quadratic Gaussian (LQG) controller and H-infinity controller . The synthesis of the two controllers is performed via experimentally estimated SIMO state space model. The 30% input multiplicative uncertainty is introduced in estimated model. In this manner, a dead-band of proportional spool valve position is taken into account. This dead-band is constructively implemented to provide safety requirements of electrohydraulic steering. The robust stability and robust performance analysis are done by determining a structured singular value (μ) of the both closed-loop control systems, which are represented in M-Δ structure. The workability of the both systems are verified through simulation and real world experiments on laboratory test rig.

The paper is focused on using the possibilities of implementing RFID technology with augmented reality. Today, it has become an element that is becoming more widely known. In this article, we gradually focus on two-second measures in two display units. The first alternative used for the measurement is the use of a UHF Bluetooth RFID reader with Smart glasses on the platform of the Android system. The second alternative is the use of industrial readers in Ethernet connection, its connection to the local wifi network and smart glasses Microsoft HoloLens 2. Both reading systems work on the principle of Ultra Hight Frequency, and therefore, different RFID tags are used in Label, industrial and metal case. For the laboratory measurements, we tested the reading distance of the RFID tag and the ability of intuitive control of applications. Based on the findings, it can be deduced that the implementation of augmented reality can help online monitoring and tracking the progress of production. As a concept, it is based on both proposals from the KANBAN system. The advantage is that suggested versions are mobile and can be directly implemented in manufacturing enterprises.