Search Results (15)

Mitigating cyberattacks on IoT networks is critical and remains a significant challenge, as such attacks can cause severe damage to the network systems and services. Moreover, the large volume of devices in IoT networks presents another challenge in managing security to reduce the risk of attacks. The Manufacturer Usage Description (MUD) is a standard for limiting attack risks on IoT networks. However, MUD has limitations, as it relies solely on pre-defined access control list (ACL) rules to allow permitted traffic and block unknown traffic. This can lead to false-negative filtering, where malicious traffic may still be allowed by MUD, compromising an entire IoT network. This study presents the implementation of a network behaviour analysis (NBA) system for DoS/DDoS attack detection in MUD-based IoT networks. We designed a set of algorithms to enhance the effectiveness of malicious traffic detection compared to using MUD alone. The NBA system groups related traffic and detects a variety of DoS/DDoS attacks that utilise TCP and MQTT protocols. Our evaluation demonstrates that the NBA system achieves high detection accuracy, effectively identifying attacks that MUD alone would not be able to detect, thereby enhancing the effectiveness of attack detection in MUD-based IoT networks. Full article

Micromobility vehicles, e-scooters and e–bicycles in particular, gain an increasing popularity but also receive criticism, mainly due to road safety issues and their carbon footprint, particularly in relation to their Li-ion batteries. Available field data are not sufficient to explore those issues. Important input variables, such as riders’ reaction time, the impact of human factors on riders’ safety, battery performance degradation with time, remain unknown. This paper presents the design, development, initial calibration and validation of two novel driving simulators, one for an e-scooter and one, for an e-bicycle. The simulators are already operational and used to acquire new knowledge on driving behavior and battery performance. By enabling a better understanding of e-vehicle performance and safety, these simulators contribute to reducing the environmental impact of micromobility by optimizing battery usage and improving vehicle design for sustainability. The paper describes the overall configuration and the main technical specifications of both simulators and provides a thorough description of all their mechanical and electromechanical components. It documents the initial calibration process before launching the experiments and presents the validation methodology with the participation of over 100 users. The outcomes of future experiments are expected to be beneficial to (i) researchers who will gain new insights on e-vehicle performance, (ii) users, enabling them to make informed decisions on vehicle choice and riding patterns, (iii) urban planners on improving urban infrastructure design, (iv) vehicle manufacturers on identifying customer needs and enhancing vehicle design for sustainability, and (v) Public Authorities on adjusting vehicle and infrastructure specifications to reduce the carbon footprint of urban mobility. Full article

The imperative for electrification of road transport, driven by global climate targets, underscores the need for innovative powertrain systems in heavy-duty vehicles. When developing new electric drive modules, individual operational requirements need to be considered instead of generalized usage profiles, as heavy-duty vehicles experience significantly differing loads depending on their field of operation. Real driving data, representing the demands of different application scenarios, offers great potential for digital replication of driving conditions at different stages of simulation and physical validation. Application- and vehicle-specific longitudinal requirements during operation are particularly relevant for the dimensioning of powertrain components. Road gradient and mass estimation assist in the description of these operating conditions, allowing for detailed modeling of the real load conditions. An incorporation of real driving data instead of solely relying on standardized cycles has the potential of tailoring components to the target lead users and applications. While some operating conditions can be recorded by vehicle manufacturers, these are usually not accessible by third parties. In this paper, the authors present an innovative methodology of estimating vehicle parameters for the generation of representative driving profiles for implementation into a consecutive powertrain design process. The approach combines the measurement of real driving data with state estimation. The authors show that the presented methodology enables the generation of driving profiles with less than 25% deviation from the original data set. Full article

Industry 4.0 emphasizes the importance of sustainable manufacturing practices. Accordingly, engineering education has increasingly incorporated virtual reality (VR) technology. This study aims to identify the potential usage of VR as an educational tool to enhance manufacturing sustainability within Industry 4.0. The methodology used an experimental design, a structured survey, and a multilevel modeling analysis to measure the effects of VR interventions. The findings show that the learning outcomes of VR treatments and post-test scores are significantly impacted by two crucial factors: age (β = 0.35, p < 0.01) and VR experience (r = 0.42, p < 0.01). Furthermore, sustainability attitudes moderately affected academic development (β = 0.25, p < 0.05). According to descriptive statistics, virtual reality treatment resulted in a 25% improvement in the post-test results. According to MLM, the combined effects of virtual reality experience and sustainability attitudes on learning outcomes account for 45% of the total variation (R² = 0.45, p < 0.01). The study’s findings highlight the importance of VR in enhancing educational outcomes and fostering sustainable production practices within Industry 4.0. This research is unique in its simultaneous investigation of VR technology, engineering education, and sustainability, providing valuable insights into how VR can contribute to preparing engineers for the challenges of Industry 4.0 and advancing sustainable initiatives in the manufacturing field. Full article

The newest technology allows the medical industry to manufacture innovative products such as milled titanium prosthodontic parts in an implant for a screw-retained suprastructure. In the literature, there are some articles on the clinical usage of subperiosteal implants, but none of these publications, either in PubMed or Google Scholar, thoroughly describe the workflow for the design and manufacture of individual implants for maxillofacial surgery with milled threads for a screw-retained prosthodontic bridge. The aim of the article is to present a step-by-step method of producing personalized implants, from the first steps of production to the implantation of the final product. The article includes information on patient qualification for surgery, computational preparation and skull printing, planning of Mai Implants^®, meshing, 3D printing and milling, cleaning, rinsing, anodizing, and laser marking, as well as the cleaning and sterilization process in a hospital or dental clinic. A detailed description of implant production allows for the analysis of each step and the development of technology. The production of implants is an expensive procedure, but considering all the advantages of the Mai Implants^® treatment and the disadvantages of alternatives, the product is worth the price. Full article

Attacks launched from IoT networks can cause significant damage to critical network systems and services. IoT networks may contain a large volume of devices. Protecting these devices from being abused to launch traffic amplification attacks is critical. The manufacturer usage description (MUD) architecture uses pre-defined stateless access control rules to allow or block specific network traffic without stateful communication inspection. This can lead to false negative filtering of malicious traffic, as the MUD architecture does not include the monitoring of communication states to determine which connections to allow through. This study presents a novel solution, the enhanced profiling assurance (EPA) architecture. It incorporates both stateless and stateful communication inspection, a unique approach that enhances the detection effectiveness of the MUD architecture. EPA contains layered intrusion detection and prevention systems to monitor stateful and stateless communication. It adopts three-way decision theory with three outcomes: allow, deny, and uncertain. Packets that are marked as uncertain must be continuously monitored to determine access permission. Our analysis, conducted with two network scenarios, demonstrates the superiority of the EPA over the MUD architecture in detecting malicious activities. Full article

Consideration of sapphire shaped crystals as the material for manufacturing of medical instruments expands the opportunities of various approaches for diagnostics, exposure and treatment. Due to physical, mechanical and chemical properties of sapphire, as well as to its complex shape, such instruments are capable to demonstrate better performance for medical applications comparing to common tools. However, the manufacturing of high quality sapphire crystal with such geometry is still a complex issue, that usually requires application of various crystal growth techniques assisted with the automated weight control system. In this work, we consider one of such cases, that is the growth of a sapphire crystal, which can be applied for cryosurgery as an applicator due to a hollow-monolithic shape transition. Its hollow part can be filled with coolant in order to enable fast freezing of biological tissue during application. For this aim, it is of high importance to exclude the appearance of inclusions during the shape transition. To overcome this problem, we suggest using of noncapillary shaping (NCS) technique of crystal growth and study the weight signal measured during the manufacturing. We obtain the analytical description of the weight signal alteration that can be used as the program equation to control the crystal shape. We experimentally demonstrate the advantage of using such crystal for cryosurgery and obtaining faster ice-ball formation inside the model gelatin-based medium in comparison with the usage of the monolithic sapphire applicator of the same diameter. The demonstrated ability can be applied for future development of cryosurgical tools, while the analytical description of the weight signal could find its application for NCS manufacturing of sapphire crystals for other purposes. Full article

Little has been studied regarding the repeated usage of healing abutments and their effects on the distortion of dental implant-healing abutment hex surfaces. Additionally, implant manufacturers do not provide specific guidelines on how many times a healing abutment can be used before discarding. Therefore, we evaluated the effect of repeated screwing-unscrewing of implant-healing abutment on the healing abutment hex surface and screw head. A total of 12 Biomate implants with 4 mm diameter and 13 mm length were inserted into a synthetic bone block. The standard healing abutments of 3 mm diameter and 4 mm length were screwed onto each implant using a torque ratchet at a final torque of 30 Ncm. Immediately, the abutments were unscrewed at 30 Ncm. Then, screwing-unscrewing was repeated for 4, 8, 16, 24, 32, 40, 80, 160, 320, and 400 times and the healing abutments were scanned under the scanning electron microscope for any distortion. Distortion was graded as 0, 1, 2, and 3. Data were analyzed using SPSS 24.0. Descriptive statistics were calculated. One-way ANOVA with post hoc using Tukey’s HSD test was performed to analyze the difference in distortion at different screwing-unscrewing times. A significant level was selected at p-value = 0.05. It was found that distortion healing abutments screws were seen after 32 times screwing and unscrewing. There was a significant difference in the distortion (p-value < 0.05) after 24 times of repeated usage of healing abutment and at 160, 320, and 400 times. No surface distortions were observed at the healing abutment screw head at 4, 8, 16, 24, 32, 40, 80, 160, 320, and 400 cycles of screwing-unscrewing. It can be concluded that repeated screwing and unscrewing of the implant-healing abutments causes damage to the healing abutment hex surface. The distortion of healing abutments screws was seen after 32 times screwing and unscrewing. No surface distortions were observed on the healing abutment screw head until 400 times of screwing and unscrewing. Hence, the clinician should be cautious while using the healing abutments repeatedly. Full article

Process planning in manufacturing today focuses on optimizing the conflicting targets of cost, quality, and time. Due to increasing social awareness and subsequent governmental regulation, environmental impact becomes a fourth major aspect. Eventually, sustainability in manufacturing ensures future competitiveness. In this paper, a framework for the planning of sustainable manufacturing is proposed. It is based on the abstraction and generalization of manufacturing resources and part descriptions, which are matched and ranked using a multi-criteria decision analysis method. Manufacturing resources provide values for cost, quality, time and environmental impacts, which multiply with their usage within a manufacturing task for a specific part. The framework is validated with a detailed modeling of a laser machine as a resource revealing benefits and optimization potential of the underlying data model. Finally, the framework is applied to a use case of a flange part with two different manufacturing strategies, i.e., laser metal-wire deposition and conventional milling. The most influential parameters regarding the environmental impacts are the raw material input, the manufacturing energy consumption and the machine production itself. In general, the framework enabled the identification of non-predetermined manufacturing possibilities and the comprehensive comparison of production resources. Full article

It has been proven in research literature that the analysis of encrypted traffic with statistical analysis and machine learning can reveal the type of activities performed by a user accessing the network, thus leading to privacy risks. In particular, different types of traffic (e.g., skype, web access) can be identified by extracting time based features and using them in a classifier. Such privacy attacks are asymmetric because a limited amount of resources (e.g., machine learning algorithms) can extract information from encrypted traffic generated by cryptographic systems implemented with a significant amount of resources. To mitigate privacy risks, studies in research literature have proposed a number of techniques, but in most cases only a single technique is applied, which can lead to limited effectiveness. This paper proposes a mitigation approach for privacy risks related to the analysis of encrypted traffic which is based on the integration of three main components: (1) A machine learning component which proactively analyzes the encrypted traffic in the network to identify potential privacy threats and evaluate the effectiveness of various mitigation techniques (e.g., obfuscation), (2) a policy based component where policies are used to enforce privacy mitigation solutions in the network and (3) a network node profile component based on the Manufacturer Usage Description (MUD) standard to enable changes in the network nodes in the cases where the first two components are not effective in mitigating the privacy risks. This paper describes the different components and how they interact in a potential deployment scenario. The approach is evaluated on the public dataset ISCXVPN2016 and the results show that the privacy threat can be mitigated significantly by removing completely the identification of specific types of traffic or by decreasing the probability of their identification as in the case of VOIP by 50%, Chat by 40% and Browsing by 33%, thus reducing significantly the privacy risk. Full article

Despite the advantages that the Internet of Things (IoT) will bring to our daily life, the increasing interconnectivity, as well as the amount and sensitivity of data, make IoT devices an attractive target for attackers. To address this issue, the recent Manufacturer Usage Description (MUD) standard has been proposed to describe network access control policies in the manufacturing phase to protect the device during its operation by restricting its communications. In this paper, we define an architecture and process to obtain and enforce the MUD restrictions during the bootstrapping of a device. Furthermore, we extend the MUD model with a flexible policy language to express additional aspects, such as data privacy, channel protection, and resource authorization. For the enforcement of such enriched behavioral profiles, we make use of Software Defined Networking (SDN) techniques, as well as an attribute-based access control approach by using authorization credentials and encryption techniques. These techniques are used to protect devices’ data, which are shared through a blockchain platform. The resulting approach was implemented and evaluated in a real scenario, and is intended to reduce the attack surface of IoT deployments by restricting devices’ communication before they join a certain network. Full article

Friction is the main phenomenon that has a huge influence on the flow behavior of deformed material in sheet metal forming operations. Sheet metal forming methods are one of the most popular processes of obtaining finished products, especially in aerospace, automobile, and defense industries. Methods of sheet forming are carried out at different temperatures. So, it requires tribological tests that suitably represent the contact phenomena related to the temperature. The knowledge of the friction properties of the sheet is required for the proper design of the conditions of manufacturing processes and tools. This paper summarizes the methods used to describe friction conditions in conventional sheet metal forming and incremental sheet forming that have been developed over a period of time. The following databases have been searched: WebofKowledge, Scopus, Baztool, Bielefield Academic Search Engine, DOAJ Directory of Open Access Journals, eLibrary.ru, FreeFullPdf, GoogleScholar, INGENTA, Polish Scientific Journals Database, ScienceDirect, Springer, WorldCat, WorldWideScience. The English language is selected as the main source of review. However, in a limited scope, databases in Polish and Russian languages are also used. Many methods of friction testing for tribological studies are selected and presented. Some of the methods are observed to have a huge potential in characterizing frictional resistance. The application of these methods and main results have also been provided. Parameters affecting the frictional phenomena and the role of friction have also been explained. The main disadvantages and limitations of the methods of modeling the friction phenomena in specific areas of material to be formed have been discussed. The main findings are as follows—The tribological tests can be classified into direct and indirect measurement tests of the coefficient of friction (COF). In indirect methods of determination, the COF is determined based on measuring other physical quantities. The disadvantage of this type of methods is that they allow the determination of the average COF values, but they do not allow measuring and determining the real friction resistance. In metal forming operations, there exist high local pressures that intensify the effects of adhesion and plowing in the friction resistance. In such conditions, due to the plastic deformation of the material tested, the usage of the formula for the determination of the COF based on the Coulomb friction model is limited. The applicability of the Coulomb friction model to determine the COF is also very limited in the description of contact phenomena in hot SMF due to the high shear of adhesion in total contact resistance. Full article

The fourth industrial revolution is being mainly driven by the integration of Internet of Things (IoT) technologies to support the development lifecycle of systems and products. Despite the well-known advantages for the industry, an increasingly pervasive industrial ecosystem could make such devices an attractive target for potential attackers. Recently, the Manufacturer Usage Description (MUD) standard enables manufacturers to specify the intended use of their devices, thereby restricting the attack surface of a certain system. In this direction, we propose a mechanism to manage securely the obtaining and enforcement of MUD policies through the use of a Software-Defined Network (SDN) architecture. We analyze the applicability and advantages of the use of MUD in industrial environments based on our proposed solution, and provide an exhaustive performance evaluation of the required processes. Full article

Automotive manufacturers are competing to be the first to introduce customer-ready autonomous vehicles. Some manufacturers are claiming to launch their first self-driving cars as early as 2020. Which all sounds very good and futuristic; however, the question arises, are customers even ready to adopt this new technological advancement? Therefore, this pilot study is aimed at finding out the answer to this question in the Austrian market. This study discovers the standpoint of Austrian consumers concerning the acceptance of self-driving cars for daily usage and gives an overview of the current point of view regarding autonomous vehicles (AVs). The data for this study was collected using an online, user-friendly, Likert scale survey. The collected data were processed and analyzed for empirical significance in SPSS using Spearman’s rank correlation and the Mann–Whitney U test supported by descriptive analysis. The results of the study indicate that Austrian consumers are well aware of autonomous vehicles and their technology. However, they have specific concerns about reliability, cybersecurity, and futuristic car-sharing models. Therefore, these concerns about AVs should be addressed by auto manufactures in order to gain consumers’ trust and sell them a new form of mobility. Full article

Extrusion is a very popular and multi-faceted manufacturing process. A large number of products for the automotive, aerospace, and construction sectors are produced through aluminum extrusion. Many defects in the extruded products occur because of the conditions of the dies and tooling. The problems in dies can be due to material issues, design and manufacturing, or severe usage. They can be avoided by maintaining the billet quality, by controlling the extrusion process parameters, and through routine maintenance. Die problems that occur on a day-to-day basis are mostly repairable and are rectified through various types of die correction operations. These defects and repair operations have not been reported in detail in the published literature. The current paper presents an in-depth description of repairable die defects and related die correction operations in metal extrusion. All major die defects are defined and classified, and their causes, preventive measures, and die correction operations are described. A brief frequency-based statistical study of die defects is also carried out to identify the most frequent die corrections. This work can be of direct benefit to plant engineers and operators and to researchers and academics in the field of metal extrusion. Full article