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Ni-based alloys are among the materials of choice in developing high-quality coatings for ambient and high temperature applications that require protection against intense wear and corrosion. The current study aims to develop and characterize NiCrBSi coatings with high wear resistance and improved adhesion to the substrate. Starting with nickel-based feedstock powders, thermally sprayed coatings were initially fabricated. Prior to deposition, the powders were characterized in terms of microstructure, particle size, chemical composition, flowability, and density. For comparison, three types of powders with different chemical compositions and characteristics were deposited onto a 1.7227 tempered steel substrate using oxyacetylene flame spraying, and subsequently, the coatings were inductively remelted. Ball-on-disc sliding wear testing was chosen to investigate the tribological properties of both the as-sprayed and induction-remelted coatings. The results reveal that, in the case of as-sprayed coatings, the main wear mechanisms were abrasive, independent of powder chemical composition, and correlated with intense wear losses due to the poor intersplat cohesion typical of flame-sprayed coatings. The remelting treatment improved the performance of the coatings in terms of wear compared to that of the as-sprayed ones, and the density and lower porosity achieved during the induction post-treatment had a significant positive role in this behavior.
Without proper post-processing (often using flame, furnace, laser remelting, and induction) or reinforcements’ addition, Ni-based flame-sprayed coatings generally manifest moderate adhesion to the substrate, high porosity, unmelted particles, undesirable oxides, or weak wear resistance and mechanical properties. The current research aimed to investigate the addition of ZrO2 as reinforcement to the self-fluxing alloy coatings. Mechanically mixed NiCrBSi-ZrO2 powders were thermally sprayed onto an industrially relevant high-grade steel. After thermal spraying, the samples were differently post-processed with a flame gun and with a vacuum furnace, respectively. Scanning electron microscopy showed a porosity reduction for the vacuum-heat-treated samples compared to that of the flame-post-processed ones. X-ray diffraction measurements showed differences in the main peaks of the patterns for the thermal processed samples compared to the as-sprayed ones, these having a direct influence on the mechanical behavior of the coatings. Although a slight microhardness decrease was observed in the case of vacuum-remelted samples, the overall low porosity and the phase differences helped the coating to perform better during wear-resistance testing, realized using a ball-on-disk arrangement, compared to the as-sprayed reference samples.
Among the FDM process variables, one of the less addressed in previous research is the filament color. Moreover, if not explicitly targeted, the filament color is usually not even mentioned.
Aiming to point out if, and to what extent, the color of the PLA filaments influences the dimensional precision and the mechanical strength of FDM prints, the authors of the present research carried out experiments on tensile specimens. The variable parameters were the layer height (0.05 mm, 0.10 mm, 0.15 mm, 0.20 mm) and the material color (natural, black, red, grey). The experimental results clearly showed that the filament color is an influential factor for the dimensional accuracy as well as for the tensile strength of the FDM printed PLA parts. Moreover, the two way ANOVA test performed revealed that the strongest effect on the tensile strength was exerted by the PLA color (2 = 97.3%), followed by the layer height (2 = 85.5%) and the interaction between the PLA color and the layer height (2 = 80.0%). Under the same printing conditions, the best dimensional accuracy was ensured by the black PLA (0.17% width deviations, respectively 5.48% height deviations), whilst the grey PLA showed the highest ultimate tensile strength values (between 57.10 MPa and 59.82 MPa).
Impact of cobalt content and grain growth inhibitors in laser-based powder bed fusion of WC-Co
(2022)
Processing of tungsten carbide‑cobalt (WC-Co) by laser-based powder bed fusion (PBF-LB) can result in characteristic microstructure defects such as cracks, pores, undesired phases and tungsten carbide (WC) grain growth, due to the heterogeneous energy input and the high thermal gradients. Besides the processing conditions, the material properties are affected by the initial powder characteristics. In this paper, the impact of powder composition on microstructure, phase formation and mechanical properties in PBF-LB of WC-Co is studied.
Powders with different cobalt contents from 12 wt.-% to 25 wt.-% are tested under variation of the laser parameters.
Furthermore, the impact of vanadium carbide (VC) and chromium (Cr) additives is investigated. Both are known as grain growth inhibitors for conventional sintering processes. The experiments are conducted at a pre-heating temperature of around 800 ◦C to prevent crack formation in the samples. Increasing laser energy input reduces porosity but leads to severe embrittlement for low cobalt content and to abnormal WC grain growth for high cobalt content. It is found that interparticular porosity at low laser energy is more severe for low cobalt content due to poor wetting of the liquid phase. Maximum bending strength of σB > 1200 MPa and Vickers hardness of approx. 1000 HV3 can be measured for samples generated from WC-Co 83/17 powder with medium laser energy input. The addition of V and Cr leads to increased formation of additional phases such as Co3W3C, Co3V and Cr23C6 and to increased lateral and multi-laminar growth of the WC grains. In contrast to conventional sintering, a grain growth inhibiting effect of V and Cr in the laser molten microstructure is not achieved.
Among all additive manufacturing processes, Directed Energy Deposition-Arc (DED-Arc) shows significantly shorter production times and is particularly suitable for large-volume components of simple to medium complexity. To exploit the full potential of this process, the microstructural, mechanical and corrosion behavior have to be studied. High stickout distances lead to a large offset, which leads to an instable electric arc and thus defects such as lack of fusion. Since corrosion preferentially occurs at such defects, the main objective of this work is to investigate the influence of the stickout distance on the corrosion
behavior and microstructure of stainless steel manufactured by DED-Arc.
Within the heterogenous structure of the manufactured samples lack of fusion defects were detected. The quantity of such defects was reduced by applying a shorter stickout distance. The corrosion behavior of the additively manufactured specimens was investigated by means of potentiodynamic polarization measurements. The semi-logarithmic current density potential curves showed a similar course and thus similar corrosion resistance like that of the conventionally forged sample. The polarization curve of the reference material shows numerous current peaks, both in the anodic and cathodic regions. This metastable behavior is induced by the presence of manganese sulfides. On the sample surface a local attack by pitting corrosion was identified.
In this study, the characteristics of HVOF sprayed WC/Co-Cr and WC/Cr3C2/Ni coatings were investigated in correlation with the variation of the powder feed rate. For this purpose, the mass flow was adjusted to four different levels. The other process parameters were all kept constant. The morphological and mechanical properties as well as the electrochemical corrosion behaviour were investigated and associated with the achieved microstructure.
Both scanning electron microscopy and confocal laser scanning microscopical images of the cross sections demonstrated a good correlation between the selected powder feed rate and the degree of internal porosity produced, which can be attributed to the deposition process. The coatings which fulfilled the requirements of the pre-qualification step were selected for further hardness measurements, tribological tests and electrochemical corrosion measurements in a 3.5 wt% NaCl aqueous solution.
It was found that the powder feed rate strongly influenced the characteristics of the HVOF-sprayed cermet coatings. The tendency to crack formation, especially at the interface coating/substrate, was lower for the samples coated with a lower mass flow rate. These studies have shown that the applied powder feed rates had an important influence on the coatings microstructure and implicitly on the sliding wear behavior respectively on the electrochemical corrosion resistance of the investigated cermet coatings.
Even though we live in a period when the word digitization is prevalent in many social areas, the COVID-19 pandemic has divided mankind into two main categories: some people have seen this crisis as an opportunity to move the activities online and, furthermore, to accelerate digitization in as many areas as possible, while others have been reluctant, keeping their preferences for face-to-face activities. The current work presents the results of an analysis on 249 students from 11 engineering faculties. The study aims to identify the impact of the COVID-19 pandemic on students’ educational experiences when switching from face-to-face to online education during a public health emergency or COVID 19-related state of alert. The overall conclusion was that, although the pandemic has brought adverse consequences on the health and life quality of many people, the challenges that humankind has been subjected to have led to personal and professional development and have opened up new perspectives for carrying out the everyday activities.
Tape brazing constitutes a cost-effective alternative surface protection technology for complex-shaped surfaces. The study explores the characteristics of high-temperature brazed coatings using a cobalt-based powder deposited on a stainless-steel substrate in order to protect parts subjected to hot temperatures in a wear-exposed environment. Microstructural imaging corroborated with x-ray diffraction analysis showed a complex phased structure consisting of intermetallic Cr-Ni, C-Co-W Laves type, and chromium carbide phases. The surface properties of the coatings, targeting hot corrosion behavior, erosion, wear resistance, and microhardness, were evaluated. The high-temperature corrosion test was performed for 100 h at 750 C in a salt mixture consisting of 25 wt.% NaCl + 75 wt.% Na2SO4. The degree of corrosion attack was closely connected with the exposure temperature, and the degradation of the material corresponding to the mechanisms of low-temperature hot corrosion. The erosion tests were carried out using alumina particles at a 90 impingement angle. The results, correlated with the microhardness measurements, have shown that Co-based coatings exhibited approximately 40% lower material loss compared to that of the steel substrate.
The printing variable least addressed in previous research aiming to reveal the effect of the FFF process parameters on the printed PLA part’s quality and properties is the filament color. Moreover, the color of the PLA, as well as its manufacturer, are rarely mentioned when the experimental conditions for the printing of the samples are described, although current existing data reveal that their influence on the final characteristics of the print should not be neglected. In order to point out the importance of this influential parameter, a natural and a black-colored PLA filament, produced by the same manufacturer, were selected. The dimensional accuracy, tensile strength, and friction properties of the samples were analyzed and compared for printing temperatures ranging from 200 C up to 240 C. The experimental results clearly showed different characteristics depending on the polymer color of samples printed under the same conditions. Therefore, the optimization of the FFF process parameters for the 3D-printing of PLA should always start with the proper selection of the type of the PLA material, regarding both its color and the fabricant.
Flame-sprayed NiCrBSi/WC-12Co composite coatings were deposited in different ratios on the surface of stainless steel. Oxyacetylene flame remelting treatment was applied to surfaces for refinement of the morphology of the layers and improvement of the coating/substrate adhesion.
The performance of the coated specimens to cavitation erosion and electrochemical corrosion was evaluated by an ultrasonic vibratory method and, respectively, by polarization measurements. The microstructure was investigated by means of scanning electron microscopy (SEM) combined with energy dispersive X-ray analysis (EDX). The obtained results demonstrated that the addition of 15 wt.% WC-12Co to the self-fluxing alloy improves the resistance to cavitation erosion (the terminal erosion rate (Vs) decreased with 15% related to that of the NiCrBSi coating) without influencing the good corrosion resistance in NaCl solution. However, a further increase in WC-Co content led to a deterioration of these coating properties (the Vs has doubled related to that of the NiCrBSi coating).
Moreover, the corrosion behavior of the latter composite coating was negatively influenced, a fact confirmed by increased values for the corrosion current density (icorr). Based on the achieved experimental results, one may summarize that NiCrBSi/WC-Co composite coatings are able to increase the life cycle of expensive, high-performance components exposed to severe cavitation conditions.
Hydrogen produced via water electrolysis powered by renewable electricity or green H2 offers new decarbonization pathways. Proton exchange membrane water electrolysis (PEMWE) is a promising technology although the current density, temperature, and H2 pressure of the PEMWE will have to be increased substantially to curtail the cost of green H2. Here, a porous transport layer for PEMWE is reported, that enables operation at up to 6 A cm−2, 90 °C, and 90 bar H2 output pressure. It consists of a Ti porous sintered layer (PSL) on a low‐cost Ti mesh (PSL/mesh‐PTL) by diffusion bonding. This novel approach does not require a flow field in the bipolar plate. When using the mesh‐PTL without PSL, the cell potential increases significantly due to mass transport losses reaching ca. 2.5 V at 2 A cm−2 and 90 °C.
In this work, a novel polymer electrolyte membrane water electrolyzer (PEMWE) test cell based on hydraulic single-cell compression is described. In this test cell, the current density distribution is almost homogeneous over the active cell area due to hydraulic cell clamping. As the hydraulic medium entirely surrounds the active cell components, it is also used to control cell temperature resulting in even temperature distribution. The PEMWE single-cell test system based on hydraulic compression offers a 25 cm2 active surface area (5.0 × 5.0 cm) and can be operated up to 80°C and 6.0 A/cm2. Construction details and material selection for the designed test cell are given in this document. Furthermore, findings related to pressure distribution analyzed by utilizing a pressure-sensitive foil, the cell performance indicated by polarization curves, and the reproducibility of results are described. Experimental data indicate the applicability of the presented testing device for relevant PEMWE component testing and material analysis.
The present paper presents one- and two-step approaches for electrochemical Pt and Ir deposition on a porous Ti-substrate to obtain a bifunctional oxygen electrode. Surface pre-treatment of the fiber-based Ti-substrate with oxalic acid provides an alternative to plasma treatment for partially stripping TiO2 from the electrode surface and roughening the topography. Electrochemical catalyst deposition performed directly onto the pretreated Ti-substrates bypasses unnecessary preparation and processing of catalyst support structures. A single Pt constant potential deposition (CPD), directly followed by pulsed electrodeposition (PED), created nanosized noble agglomerates. Subsequently, Ir was deposited via PED onto the Pt sub-structure to obtain a successively deposited PtIr catalyst layer. For the co-deposition of PtIr, a binary PtIr-alloy electrolyte was used applying PED. Micrographically, areal micro- and nano-scaled Pt sub-structure were observed, supplemented by homogenously distributed, nanosized Ir agglomerates for the successive PtIr deposition. In contrast, the PtIr co-deposition led to spherical, nanosized PtIr agglomerates. The electrochemical ORR and OER activity showed increased hydrogen desorption peaks for the Pt-deposited substrate, as well as broadening and flattening of the hydrogen desorption peaks for PtIr deposited substrates. The anodic kinetic parameters for the prepared electrodes were found to be higher than those of a polished Ir-disc.
For proton exchange membrane water electrolysis (PEMWE) to become competitive, the cost of stack components, such as bipolar plates (BPP), needs to be reduced. This can be achieved by using coated low-cost materials, such as copper as alternative to titanium. Herein we report on highly corrosion-resistant copper BPP coated with niobium. All investigated samples showed excellent corrosion resistance properties, with corrosion currents lower than 0.1 µA cm−2 in a simulated PEM electrolyzer environment at two different pH values. The physico-chemical properties of the Nb coatings are thoroughly characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM). A 30 µm thick Nb coating fully protects the Cu against corrosion due to the formation of a passive oxide layer on its surface, predominantly composed of Nb2O5. The thickness of the passive oxide layer determined by both EIS and XPS is in the range of 10 nm. The results reported here demonstrate the effectiveness of Nb for protecting Cu against corrosion, opening the possibility to use it for the manufacturing of BPP for PEMWE. The latter was confirmed by its successful implementation in a single cell PEMWE based on hydraulic compression technology.
Unsupervised physics-informed deep learning can be used to solve computational physics problems by training neural networks to satisfy the underlying equations and boundary conditions without labeled data. Parameters such as network architecture and training method determine the training success. However, the best choice is unknown a priori as it is case specific. Here, we investigated network shapes, sizes, and types for unsupervised physics-informed deep learning of the two-dimensional Reynolds averaged flow around cylinders. We trained mixed-variable networks and compared them to traditional models. Several network architectures with different shape factors and sizes were evaluated. The models were trained to solve the Reynolds averaged Navier-Stokes equations incorporating Prandtl’s mixing length turbulence model. No training data were deployed to train the models. The superiority of the mixed-variable approach was confirmed for the investigated high Reynolds number flow. The mixed-variable models were sensitive to the network shape. For the two cylinders, differently deep networks showed superior performance. The best fitting models were able to capture important flow phenomena such as stagnation regions, boundary layers, flow separation, and recirculation. We also encountered difficulties when predicting high Reynolds number flows without training data.
Advancements in hand-drawn chemical structure recognition through an enhanced DECIMER architecture
(2024)
Accurate recognition of hand-drawn chemical structures is crucial for digitising hand-written chemical information in traditional laboratory notebooks or facilitating stylus-based structure entry on tablets or smartphones. However, the inherent variability in hand-drawn structures poses challenges for existing Optical Chemical Structure Recognition (OCSR) software. To address this, we present an enhanced Deep lEarning for Chemical ImagE Recognition (DECIMER) architecture that leverages a combination of Convolutional Neural Networks (CNNs) and Transformers to improve the recognition of hand-drawn chemical structures. The model incorporates an EfficientNetV2 CNN encoder that extracts features from hand-drawn images, followed by a Transformer decoder that converts the extracted features into Simplified Molecular Input Line Entry System (SMILES) strings. Our models were trained using synthetic hand-drawn images generated by RanDepict, a tool for depicting chemical structures with different style elements. A benchmark was performed using a real-world dataset of hand-drawn chemical structures to evaluate the model's performance. The results indicate that our improved DECIMER architecture exhibits a significantly enhanced recognition accuracy compared to other approaches.
An Augmented Multiphase Rail Launcher With a Modular Design: Extended Setup and Muzzle Fed Operation
(2024)
With ongoing developments in the field of smart cities and digitalization in general, data is becoming a driving factor and value stream for new and existing economies alike. However, there exists an increasing centralization and monopolization of data holders and service providers, especially in the form of the big US-based technology companies in the western world and central technology providers with close ties to the government in the Asian regions. Self Sovereign Identity (SSI) provides the technical building blocks to create decentralized data-driven systems, which bring data autonomy back to the users. In this paper we propose a system in which the combination of SSI and token economy based incentivisation strategies makes it possible to unlock the potential value of data-pools without compromising the data autonomy of the users.
The European General Data Protection Regulation (GDPR), which went into effect in May 2018, brought new rules for the processing of personal data that affect many business models, including online advertising. The regulation’s definition of personal data applies to every company that collects data from European Internet users. This includes tracking services that, until then, argued that they were collecting anonymous information and data protection requirements would not apply to their businesses.
Previous studies have analyzed the impact of the GDPR on the prevalence of online tracking, with mixed results. In this paper, we go beyond the analysis of the number of third parties and focus on the underlying information sharing networks between online advertising companies in terms of client-side cookie syncing. Using graph analysis, our measurement shows that the number of ID syncing connections decreased by around 40 % around the time the GDPR went into effect, but a long-term analysis shows a slight rebound since then. While we can show a decrease in information sharing between third parties, which is likely related to the legislation, the data also shows that the amount of tracking, as well as the general structure of cooperation, was not affected. Consolidation in the ecosystem led to a more centralized infrastructure that might actually have negative effects on user privacy, as fewer companies perform tracking on more sites.
In the modern Web, service providers often rely heavily on third parties to run their services. For example, they make use of ad networks to finance their services, externally hosted libraries to develop features quickly, and analytics providers to gain insights into visitor behavior.
For security and privacy, website owners need to be aware of the content they provide their users. However, in reality, they often do not know which third parties are embedded, for example, when these third parties request additional content as it is common in real-time ad auctions.
In this paper, we present a large-scale measurement study to analyze the magnitude of these new challenges. To better reflect the connectedness of third parties, we measured their relations in a model we call third party trees, which reflects an approximation of the loading dependencies of all third parties embedded into a given website. Using this concept, we show that including a single third party can lead to subsequent requests from up to eight additional services. Furthermore, our findings indicate that the third parties embedded on a page load are not always deterministic, as 50 % of the branches in the third party trees change between repeated visits. In addition, we found that 93 % of the analyzed websites embedded third parties that are located in regions that might not be in line with the current legal framework. Our study also replicates previous work that mostly focused on landing pages of websites. We show that this method is only able to measure a lower bound as subsites show a significant increase of privacy-invasive techniques. For example, our results show an increase of used cookies by about 36 % when crawling websites more deeply.
Advanced Persistent Threats (APTs) are one of the main challenges in modern computer security. They are planned and performed by well-funded, highly-trained and often state-based actors. The first step of such an attack is the reconnaissance of the target. In this phase, the adversary tries to gather as much intelligence on the victim as possible to prepare further actions. An essential part of this initial data collection phase is the identification of possible gateways to intrude the target.
In this paper, we aim to analyze the data that threat actors can use to plan their attacks. To do so, we analyze in a first step 93 APT reports and find that most (80 %) of them begin by sending phishing emails to their victims. Based on this analysis, we measure the extent of data openly available of 30 entities to understand if and how much data they leak that can potentially be used by an adversary to craft sophisticated spear phishing emails. We then use this data to quantify how many employees are potential targets for such attacks. We show that 83 % of the analyzed entities leak several attributes of uses, which can all be used to craft sophisticated phishing emails.
The set of transactions that occurs on the public ledger of an Ethereum network in a specific time frame can be represented as a directed graph, with vertices representing addresses and an edge indicating the interaction between two addresses.
While there exists preliminary research on analyzing an Ethereum network by the means of graph analysis, most existing work is focused on either the public Ethereum Mainnet or on analyzing the different semantic transaction layers using static graph analysis in order to carve out the different network properties (such as interconnectivity, degrees of centrality, etc.) needed to characterize a blockchain network. By analyzing the consortium-run bloxberg Proof-of-Authority (PoA) Ethereum network, we show that we can identify suspicious and potentially malicious behaviour of network participants by employing statistical graph analysis. We thereby show that it is possible to identify the potentially malicious
exploitation of an unmetered and weakly secured blockchain network resource. In addition, we show that Temporal Network Analysis is a promising technique to identify the occurrence of anomalies in a PoA Ethereum network.
This paper analyses the status quo of large-scale decision making combined with the possibility of blockchain as an underlying decentralized architecture to govern common pool resources in a collective manner and evaluates them according to their requirements and features (technical and non-technical). Due to an increasing trend in the distribution of knowledge and an increasing amount of information, the combination of these decentralized technologies and approaches, can not only be beneficial for consortial governance using blockchain but can also help communities to govern common goods and resources. Blockchain and its trust-enhancing properties can potenitally be a catalysator for more collaborative behavior among participants and may lead to new insights about collective action and CPRs.
Software updates take an essential role in keeping IT environments secure. If service providers delay or do not install updates, it can cause unwanted security implications for their environments. This paper conducts a large-scale measurement study of the update behavior of websites and their utilized software stacks. Across 18 months, we analyze over 5.6M websites and 246 distinct client- and server-side software distributions. We found that almost all analyzed sites use outdated software. To understand the possible security implications of outdated software, we analyze the potential vulnerabilities that affect the utilized software. We show that software components are getting older and more vulnerable because they are not updated. We find that 95 % of the analyzed websites use at least one product for which a vulnerability existed.
A Crypto-Token Based Charging Incentivization
Scheme for Sustainable Light Electric Vehicle
Sharing
(2021)
The ecological impact of shared light electric vehicles (LEV) such as kick scooters is still widely discussed. Especially the fact that the vehicles and batteries are collected using diesel vans in order to charge empty batteries with electricity of unclear origin is perceived as unsustainable. A better option could be to let the users charge the vehicles themselves whenever it is necessary. For this, a decentralized,flexible and easy to install network of off-grid solar charging stations could bring renewable electricity where it is needed without sacrificing the convenience of a free float sharing system. Since the charging stations are powered by solar energy the most efficient way to utilize them would be to charge the vehicles when the sun is shining. In order to make users charge the vehicle it is necessary to provide some form of benefit for
them doing so. This could be either a discount or free rides. A
particularly robust and well-established mechanism is controlling incentives via means of blockchain-based cryptotokens. This paper demonstrates a crypto-token based scheme for incentivizing users to charge sharing vehicles during times of considerable solar irradiation in order to contribute to more sustainable mobility services.
Self-Sovereign Identity (SSI) sorgt für eine sichere und vertrauenswürdige Digitalisierung. Nutzer können selbstbestimmt ihre digitale Identität und Nachweise wie Ausweis oder Bescheinigungen an Anwendungen weitergeben. Das europäische SSI-Ökosystem löst Abhängigkeiten von Monopolisten und gibt uns die Freiheit, die digitale Zukunft souverän und zügig zu gestalten.
Third-party tracking is a common and broadly used technique on the Web. Different defense mechanisms have emerged to counter these practices (e.g. browser vendors that ban all third-party cookies). However, these countermeasures only target third-party trackers and ignore the first party because the narrative is that such monitoring is mostly used to improve the utilized service (e.g. analytical services). In this paper, we present a large-scale measurement study that analyzes tracking performed by the first party but utilized by a third party to circumvent standard tracking preventing techniques. We visit the top 15,000 websites to analyze first-party cookies used to track users and a technique called “DNS CNAME cloaking”, which can be used by a third party to place first-party cookies. Using this data, we show that 76% of sites effectively utilize such tracking techniques. In a long-running analysis, we show that the usage of such cookies increased by more than 50% over 2021.
Web measurement studies can shed light on not yet fully understood phenomena and thus are essential for analyzing how the modern Web works. This often requires building new and adjustinng existing crawling setups, which has led to a wide variety of analysis tools for different (but related) aspects. If these efforts are not sufficiently documented, the reproducibility and replicability of the measurements may suffer—two properties that are crucial to sustainable research. In this paper, we survey 117 recent research papers to derive best practices for Web-based measurement studies and specify criteria that need to be met in practice. When applying these criteria to the surveyed papers, we find that the experimental setup and other aspects essential to reproducing and replicating results are often missing. We underline the criticality of this finding by performing a large-scale Web measurement study on 4.5 million pages with 24 different measurement setups to demonstrate the influence of the individual criteria. Our experiments show that slight differences in the experimental setup directly affect the overall results and must be documented accurately and carefully.
Momentan ist der Tenor der meisten Artikel zum Thema Künstliche Intelligenz (KI) relativ konformistisch – unverzüglich wird der Leser dahingehend sensibilisiert, dass sich hierdurch enorme Chancen auftun, die nicht ungenutzt bleiben dürfen, um international nicht abgehängt zu werden. Eher nebenbei erwähnt wird, dass trotz aller Euphorie auch die Risiken in Betracht zu ziehen seien. Da aus diesen jedoch Implikationen für die gesamte Gesellschaft resultieren können, ist es nicht nur ratsam, sondern erforderlich den Einsatz von KI in allen Bereichen – sogar im Kontext der IT-Sicherheit – unter ethischen Aspekten zu bewerten.
Als Identifikations- und Authentisierungsverfahren gewinnen biometrische Systeme immer mehr an Bedeutung. Waren sie bisher eher nur aus Filmen bekannt, wo sie für einen kleinen Mitarbeiterkreis als Zugangskontrolle zu wichtigen Räumen oder Tresoren mit kostbaren Inhalten dienten, finden biometrische Systeme immer mehr Einzug in unseren Alltag. Im elektronischem Pass ist die Speicherung biometrischer Daten bereits Pflicht. Im öffentlichen und kommerziellen Bereich werden biometrische Systeme immer mehr als zusätzliche Option angeboten, um den Zugriff auf Daten, Dienste und den Zutritt zu Räumen zu kontrollieren. Mit der Entsperrung des Smartphones sind biometrische Systeme auch im privaten Bereich angekommen. Erschwingliche Sensoren machen es sogar möglich, privat biometrische Systeme zu entwickeln.
In dieser Arbeit wird eine ganzheitliche Bedrohung für Business-Chat-Anwendungen aufgezeigt und bewertet: Chishing – Phishing über Business-Chats. Die Bedrohung hat ihren Ursprung in den Anfängen der heutigen vernetzten Welt und das zugrunde liegende Problem wird als Spoofing in seiner einfachsten Form bezeichnet. In vier von sechs Business-Chat-Tools, die in dieser Arbeit analysiert werden, ist es möglich, Anzeigenamen, Profilbilder und weitere persönliche Informationen erfolgreich zu fälschen. Dies stellt eine Bedrohung für Unternehmen dar, da es Insider-Bedrohungen Vorschub leistet und unter Umständen auch externen Entitäten dazu einlädt, sich als interne Mitarbeiterin auszugeben.
Aufgrund der zunehmenden IT-Technisierung und damit einhergehend stetigen Veränderung der Lebensbedingungen ist es notwendig, dass Menschen den IT-Lösungen und Unternehmen weiterhin und kontinuierlich vertrauen können. Denn durch den höheren Grad der IT-Technisierung steigt die Komplexität, wodurch es für den Nutzer zunehmend schwieriger wird, einzelne IT-Lösungen und deren Hintergründe zu verstehen sowie zu bewerten. Diese Veränderung hat Auswirkungen: Zum einen macht sie grundsätzlich den Nutzern – den Menschen – Angst, da gewohnte Vorgänge beständig ihre Gültigkeit verlieren. Zum anderen entsteht dadurch sowie durch die Komplexität latent das Gefühl, eine falsche Entscheidung zu treffen, weil nicht alles bedacht werden kann. So fällt dem Aspekt der Interdependenz von Vertrauen und Vertrauenswürdigkeit für deutsche und europäische Unternehmen eine hohe Bedeutung zu, insbesondere auch da sich internationale Tech-Unternehmen zunehmend weniger vertrauenswürdig im komplexen Cyber-Raum verhalten. Dies eröffnet die Möglichkeit, sich über den Aufbau von Vertrauen weltweit gegen internationale Unternehmen nachhaltig zu profilieren und positionieren. Um dieses Ziel zu realisieren, bedarf es einer strategischen Vorgehensweise – zum Beispiel auf Basis des Vertrauenswürdigkeitsmodells.
Der Plan ist klar nachvollziehbar und notwendig: Unrechtmäßig genutzte, urheberrechtlich geschützte oder gar illegale Inhalte dürfen im Internet keine Plattform zur Verbreitung finden. Bisher geschieht das durch Analyse bereits hochgeladener Inhalte. Die Europäische Union möchte aber am liebsten verhindern, dass entsprechendes Material überhaupt ins Netz gelangt. Das ruft sogenannte Upload-Filter auf den Plan, die bereits beim Versuch des Hochladens eine Blockade setzen. So weit, so gut, jedoch lassen sich durch solche Filter zu leicht auch „unliebsame“ Inhalte blockieren – Kritikern solcher Pläne scheint ein Machtmissbrauch durch Kontrolle der zur Veröffentlichung freigegebenen Inhalte vorprogrammiert. Vor diesem Hintergrund beleuchtet folgender Beitrag den Sinn, die technische Umsetzung und Machbarkeit sowie die Risiken von Upload-Filtern.
Das Internet als weltweites Netzwerk von Servern dient schon lange nicht mehr rein der Beschaffung von Informationen oder der persönlichen Kommunikation. Es werden vermehrt mediale Inhalte (Bilder, Audio- und Videodateien) in sozialen Netzwerken gepostet. Ein Großteil dieser Inhalte dient der Selbstdarstellung des Nutzers in Chroniken, Timelines, Stories etc. Allein auf Facebook werden pro Tag etwa 350 Millionen Bilder und 100 Millionen Stunden Videomaterial von Nutzern hochgeladen. Bei YouTube sind es sogar 400 Stunden Videomaterial pro Minute.
In dieser Masse von Daten sind auch unrechtmäßig genutzte, urheberrechtlich geschützte oder illegale Inhalte vorhanden. Diese unerwünschten Inhalte können mit voller Absicht oder aus Versehen und ohne kriminellen Hintergedanken hochgeladen werden. Doch egal aus welchem Grund, solche Inhalte müssen so früh wie möglich entdeckt und gelöscht werden oder sollten gar nicht erst hochgeladen werden können. Aktuelle Lösungen basieren auf einer nachträglichen Erkennung bereits hochgeladener Inhalte durch Erkennungswerkzeuge oder den Menschen.
Dieses Vorgehen ist bereits etabliert und allseits anerkannt. Eine Erweiterung durch gesetzliche Vorgaben, die das Melden, Deaktivieren und Prüfen vereinfacht und beschleunigt, wäre hier ein logischer nächster Schritt. Doch eine Prüfung und Bewertung aller Inhalte von Uploads während des Upload-Prozesses in Echtzeit wird zurzeit favorisiert und stellt eine neue, besondere Herausforderung dar.
Daher könnten in Zukunft Upload-Filter weltweit zum Einsatz kommen. Bild 1 zeigt schematisch den Unterschied zwischen einem Upload ohne Upload-Filter – links unten – und einem Upload mit Upload-Filter – links oben. Hierbei ist die Verbindung des Upload-Filters mit dem Internet nicht obligatorisch.
Ein Upload-Filter wird als eigenständige, unumgängliche Instanz in den Upload-Prozesses integriert. Seine Aufgabe besteht in der Klassifizierung der Inhalte von Uploads.
Kriterien hierfür sind vor allem das Bestehen eines Urheberschutzes für den Upload von Musik, Bildern oder Filmen, und ein eventueller Konflikt mit dem Strafrecht – zum Beispiel Kinderpornografie oder Rassismus.
Vorangetrieben wurde das Thema von der EU – genauer durch die Richtlinie (EU) 2019/790. Der hierin enthaltene Artikel 17 sieht vor, die Plattformen zu verpflichten, Lizenzverträge mit den Inhabern von Urheberrechten zu schließen. Kommen diese nicht zustande, muss die Plattform dafür sorgen, dass entsprechende Inhalte nicht hochgeladen und veröffentlicht werden können. Dieser Artikel war und ist immer noch hoch umstritten. Die EU will damit die unerlaubte Nutzung urheberrechtlich geschützter Werke auf Webseiten verhindern.
Kritiker sehen darin das freie Internet durch eine Zensurmöglichkeit in Gefahr, sollte eine diktatorische Regierung Einfluss aufdie Upload-Filter haben.
Digitalisierung gilt als die Basis für das Wohlergehen der modernen und globalen Informations- und Wissensgesellschaft. Während sie immer mehr Fahrt aufnimmt, zeigt sie gleichzeitig immer deutlicher auch ihre Kehrseite: Altbewährte Verteidigungssysteme gegen Cyberangriffe versagen zunehmend. Die Ursachen werden inzwischen sehr klar: Der klassische Perimeter löst sich dank Cloud und Mobility auf, die Angriffsflächen werden dank unzähliger neu im Netz hinzugekommener Dinge exponentiell größer, und Abwehrmaßnahmen auf herkömmliche Weise dank einer zerklüfteten, kaum integrierten Security-Landschaft immer komplexer. Zeit, die Erfolgsfaktoren der Digitalisierung zu erkennen und für das eigene Unternehmen umzusetzen. Dabei helfen vier grundsätzliche Cybersicherheitsstrategien.
Ein professionelles Digital-Risk-Management-System scannt das Clearnet, Deep Net und Darknet nach auffälligen, potenziell sensiblen Dokumenten und Informationen, um Hinweise für technische oder menschliche Sicherheitsrisiken identifizieren zu können. Die Prävention von Cyberangriffen ist nach wie vor eine entscheidend wichtige Säule, um die Digitalisierung zu meistern, Geschäftswerte langfristig zu schützen und die Anzahl an kritischen Sicherheitslücken im Unternehmen gering zu halten. Im Rahmen eines Master-Projekts hat sich das Institut für Internet-Sicherheit – if(is) mit dem Thema DRM auseinander gesetzt und insbesondere das Tool RISKREX exemplarisch analysiert.
Die Notwendigkeit von Nachweisen findet sich in sehr vielen Bereichen unseres Lebens. Zertifikate, Zeugnisse, Abnahmen, Rechnungen, Quittungen, Urkunden und Bescheinigungen über Fortbildungen sind nur einige Beispiele dafür. Durch die Digitalisierung, die mittlerweile so gut wie überall Einzug gehalten hat, und durch die Corona-Krise einen besonderen Schub erfahren hat, wird die Umsetzung solcher Nachweise heutzutage immer öfters digital statt auf Papier verwirklicht. Digitale Nachweise bieten viel Raum für die Optimierung von Prozessen und liefern gleichzeitig einige Schwachstellen, die zum Betrügen genutzt werden können.
Hier gilt es in der aktuellen Forschung und Entwicklung Lösungen zu finden, die die Sicherheit erhöhen, um somit die Vertrauenswürdigkeit der digitalen Nachweise zu steigern. Ob wir je komplett auf Papier verzichten werden können ist fraglich, jedoch kein unmögliches Ziel. Wer dieses Ziel verfolgt, muss nach und nach die Schwachstellen und Probleme der digitalen Nachweise ausmerzen.