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OpenPGP is one of the two major standards for end-to-end email security. Several studies showed that serious usability issues exist with tools implementing this standard. However, a widespread assumption is that expert users can handle these tools and detect signature spoofing attacks. We present a user study investigating expert users' strategies to detect signature spoofing attacks in Thunderbird. We observed 25 expert users while they classified eight emails as either having a legitimate signature or not. Studying expert users explicitly gives us an upper bound of attack detection rates of all users dealing with PGP signatures. 52% of participants fell for at least one out of four signature spoofing attacks. Overall, participants did not have an established strategy for evaluating email signature legitimacy. We observed our participants apply 23 different types of checks when inspecting signed emails, but only 8 of these checks tended to be useful in identifying the spoofed or invalid signatures. In performing their checks, participants were frequently startled, confused, or annoyed with the user interface, which they found supported them little. All these results paint a clear picture: Even expert users struggle to verify email signatures, usability issues in email security are not limited to novice users, and developers may need proper guidance on implementing email signature GUIs correctly.
A NEAT Way to Browse the Web
(2017)
A New Fast Algorithm for Connecting the INET Simulation Framework to Applications in Real-time
(2011)
Teaching People to program is a crucial requirement for our society to deal with the complexity of 21st-century challenges. In many teaching systems, the student is required to use a particular programming language or development environment. This paper presents an intelligent tutoring system to support blended learning scenarios, where the students can choose their programming language and development environment. For that, the system provides an interface where the students request test data and submit results to unit test their algorithms. The submitted results are analyzed by a machine learning system that detects common errors and provides adaptive feedback to the student. With this system, we are focusing on teaching algorithms rather than specific programming language semantics. The technical evaluation tested with the implementation of Mean and Median algorithm shows that the system can distinguish between error cases with an error rate under 20%. A first survey, with a small group of students, shows that the system helps them detect common errors and arrive at a correct/valid solution. We are in the process of testing the system with a larger group of students for gathering statistically reliable data.
Quick UDP Internet Connections (QUIC) is a novel transport protocol introducing known features in a new protocol design. To investigate these features and the design, we developed a QUIC implementation in the INET simulation model suite.
In this paper, we describe that implementation, its validation and a result achieved using the simulation model. The result shows the negative impact on throughput, when raising the acknowledgment ratio. We propose a solution and describe how it solves the issue.
About Nuclear Resonant Reaction Analysis for Hydrogen Investigations in Amorphous Silicon Layers
(2015)
Additional Policies for the Partially Reliable Stream Control Transmission Protocol Extension
(2015)
Adiabatic Switching and Power Dissipation of Dynamic Resonant Tunneling Device Logic Circuits
(1998)
An improvement on a concept for all optical mag- netometry using nitrogen vacancies in diamond is presented. The concept is based on the fluorescence attenuation of optically pumped nitrogen vacancies by magnetic fields up to ≈ 50 mT. The attenuation is registered by modulating the pumping power to generate a constant signal at a photodetector. A sensitivity of 2.6μT/√Hz at a sampling frequency of 500 Hz is achieved.
ALPACA: Application Layer Protocol Confusion - Analyzing and Mitigating Cracks in TLS Authentication
(2021)
The subject of this paper is the analysis of various switching electronics for batteries with separate electrodes for charging and discharging. The aim is to find a switching method that is energy-efficient on the one hand, but also economically viable on the other. Both relays and MOSFETs are suitable for switching between the electrodes. Both variants have advantages and disadvantages. The results show that a solution with MOSFETs is generally more energy-efficient, but requires a large number of cycles to be economically viable compared to the relay.
Background: Modern healthcare devices can be connected to computer networks and many western healthcareinstitutions run those devices in networks. At the same time, cyber attacks are on the rise and there is evidence thatcybercriminals do not spare critical infrastructure such as major hospitals, even if they endanger patients. Intuitively,the more and closer connected healthcare devices are to public networks, the higher the risk of getting attacked.
Methods: To asses the current connectivity status of healthcare devices, we surveyed the field of German hospitalsand especially University Medical Center UMCs.
Results: The results show a strong correlation between the networking degree and the number of medical devices.The average number of medical devices is 25.150, with a median of networked medical devices of 3.600. Actual keyusers of networked medical devices are the departments Radiology, Intensive Care, Radio-Oncology RO, NuclearMedicine NUC, and Anaesthesiology in the group of UMCs. In the next five years, the usage of networked medicaldevices will increase significantly in the departments of Surgery, Intensive Care, and Radiology. We detected a strongcorrelation between the degree of connectivity and the likelihood of being attacked.The survey answers regarding the cyber security status reveal a lack of security basics in some of the inquiredhospitals. We did discover successful attacks in hospitals with separated or subsidiary departments. A fusion ofcompetencies on an organizational level facilitates the right behavior here. Most hospitals rated themselvespredominantly positively in the self-assessment but also stated the usefulness of IT security insurance.Conclusions:Concluding our results, hospitals are already facing the consequences of omitted measures within theirgrowing pool of medical devices. Continuously relying on historically grown structures without adaption and trustingmanufactures to solve vectors is a critical behavior that could seriously endanger patients.
Asynchronous Circuit Design Based on the RTBT Monostable-Bistable-Logic-Transiton-Element (MOBILE)
(2002)
Automatic Classification of Left Ventricular Wall Segments in Small Animal Ultrasound Imaging.
(2014)
The demand for energy storage is increasing massively due to the electrification of transport and the expansion of renewable energies. Current battery technologies cannot satisfy this growing demand as they are difficult to recycle, as the necessary raw materials are mined under precarious conditions, and as the energy density is insufficient. Metal–air batteries offer a high energy density as there is only one active mass inside the cell and the cathodic reaction uses the ambient air. Various metals can be used, but zinc is very promising due to its disposability and non-toxic behavior, and as operation as a secondary cell is possible. Typical characteristics of zinc–air batteries are flat charge and discharge curves. On the one hand, this is an advantage for the subsequent power electronics, which can be optimized for smaller and constant voltage ranges. On the other hand, the state determination of the system becomes more complex, as the voltage level is not sufficient to determine the state of the battery. In this context, electrochemical impedance spectroscopy is a promising candidate as the resulting impedance spectra depend on the state of charge, working point, state of aging, and temperature. Previous approaches require a fixed operating state of the cell while impedance measurements are being performed. In this publication, electrochemical impedance spectroscopy is therefore combined with various machine learning techniques to also determine successfully the state of charge during charging of the cell at non-fixed charging currents.
Keywords:
electrochemical impedance spectroscopy; artificial neural networks; support vector regression; zinc-air battery; state estimation; state of charge
Technical and organizational steps are necessary to mitigate cyber threats and reduce risks. Human behavior is the last line of defense for many hospitals and is considered as equally important as technical security. Medical staff must be properly trained to perform such procedures. This paper presents the first qualitative, interdisciplinary research on how members of an intermediate care unit react to a cyberattack against their patient monitoring equipment. We conducted a simulation in a hospital training environment with 20 intensive care nurses. By the end of the experiment, 12 of the 20 participants realized the monitors’ incorrect behavior. We present a qualitative behavior analysis of high performing participants (HPP) and low performing participants (LPP). The HPP showed fewer signs of stress, were easier on their colleagues, and used analog systems more often than the LPP. With 40% of our participants not recognizing the attack, we see room for improvements through the use of proper tools and provision of adequate training to prepare staff for potential attacks in the future.
Das Tutorial erläutert die Elemente von Bildverarbeitungssystemen. Es befaßt sich mit den Prinzipen der Beleuchtung, Optik, Kamerasystemen und Bilderfassungskarten (Framegrabber) als Komponenten der Bildgebung und -erfassung. Weiterhin stellt sich die Bildverarbeitung als ein Gebiet der zweidimensionalen digitalen Signalverarbeitung dar. Im Verlauf des Tutorials wird daher auch auf die Grundlagen der Bilddigitalisierung und Bilddarstellung im Rechner und ihr Einfluß auf die Bildauswertung eingegangen. So kann die Verarbeitung von Bildern durch den Rechner mittels ikonischer Bildverarbeitung, also die Handhabung Bilddaten als Repräsentation von Helligkeitsinformationen, durchgeführt werden. Die Verfahren basierend auf Punktoperationen, lokale Operationen und globale Operationen z.B. zur Kontrastverbesserung, zur Rauschbefreiung oder Strukturfindung sind Methoden der ikonischen Bildanalyse. Im Rahmen des Tutorials werden die Grundlagen und Methoden der ikonischen Bildverarbeitung am Beispiel industrieller Aufgabenstellungen und Anwendungen erläutert. Die symbolische Bildverarbeitung basiert hingegen auf extrahierten Bildmerkmalen, wie z.B. Umfang, Schwerpunkt, Form etc. Ein Merkmalsvektor, gebildet aus solchen Kenngrößen stellt eine symbolische Beschreibung von Bildinhalten dar und kann z.B. zur Objektklassifikation verwendet werden.
Body energy harvesting for WSN. State of art and examples
Cache Attacks on Intel SGX
(2017)
Camera based path planning for low quantity - high variant manufacturing with industrial robots
(2019)
The acquisition costs for industrial robots have been steadily decreasing in past years. Nevertheless, they still face significant drawbacks in the required effort for the preparation of complex robot tasks which causes these systems to be rarely present so far in small and medium-sized enterprises (SME) that focus mainly on small volume, high variant manufacturing. In this paper, we propose a camera-based path planning framework that allows the fast preparation and execution of robot tasks in dynamic environments which leads to less planning overhead, fast program generation and reduced cost and hence overcomes the major impediments for the usage of industrial robots for automation in SMEs with focus on low volume and high variant manufacturing. The framework resolves existing problems in different steps. The exact position and orientation of the workpiece are determined from a 3D environment model scanned by an optical sensor. The so retrieved information is used to plan a collision-free path that meets the boundary conditions of the specific robot task. Experiments show the potential and effectiveness of the the framework presented here by evaluating a case study.
Capacitance-voltage spectroscopy and analysis of dielectric intrinsic amorphous silicon thin films
(2016)
Cathode ray-luminescent phosphor and method for the preparation thereof, <b>United States Patent</b>
(2000)
Quantum magnetometry based on optically detected magnetic resonance (ODMR) of nitrogen vacancy centers in diamond nano or microcrystals is a promising technology for sensitive, integrated magnetic-field sensors. Currently, this technology is still cost-intensive and mainly found in research. Here we propose one of the smallest fully integrated quantum sensors to date based on nitrogen vacancy (NV) centers in diamond microcrystals. It is an extremely cost-effective device that integrates a pump light source, photodiode, microwave antenna, filtering and fluorescence detection. Thus, the sensor offers an all-electric interface without the need to adjust or connect optical components. A sensitivity of 28.32nT/Hz−−−√ and a theoretical shot noise limited sensitivity of 2.87 nT/Hz−−−√ is reached. Since only generally available parts were used, the sensor can be easily produced in a small series. The form factor of (6.9 × 3.9 × 15.9) mm3 combined with the integration level is the smallest fully integrated NV-based sensor proposed so far. With a power consumption of around 0.1W, this sensor becomes interesting for a wide range of stationary and handheld systems. This development paves the way for the wide usage of quantum magnetometers in non-laboratory environments and technical applications.
Concept and Prototyping of a Fault Management Framework for Automotive Safety Relevant Systems
(2007)
Vulnerabilities in private networks are difficult to detect for attackers outside of the network. While there are known methods for port scanning internal hosts that work by luring unwitting internal users to an external web page that hosts malicious JavaScript code, no such method for detailed and precise service identification is known. The reason is that the Same Origin Policy (SOP) prevents access to HTTP responses of other origins by default. We perform a structured analysis of loopholes in the SOP that can be used to identify web applications across network boundaries. For this, we analyze HTML5, CSS, and JavaScript features of standard-compliant web browsers that may leak sensitive information about cross-origin content. The results reveal several novel techniques, including leaking JavaScript function names or styles of cross-origin requests that are available in all common browsers. We implement and test these techniques in a tool called CORSICA. It can successfully identify 31 of 42 (74%) of web services running on different IoT devices as well as the version numbers of the four most widely used content management systems WordPress, Drupal, Joomla, and TYPO3. CORSICA can also determine the patch level on average down to three versions (WordPress), six versions (Drupal), two versions (Joomla), and four versions (TYPO3) with only ten requests on average. Furthermore, CORSICA is able to identify 48 WordPress plugins containing 65 vulnerabilities. Finally, we analyze mitigation strategies and show that the proposed but not yet implemented strategies Cross-Origin Resource Policy (CORP)} and Sec-Metadata would prevent our identification techniques.
DARP is a new protocol proposal with some interesting features like dynamic roles and the use of virtual sub-networks. This article discusses about the wireless sensor network state of art and presents some desirable features in order to adapt these networks to new scenarios. These necessities are quite important to expand the applicability of wireless sensor networks and for this reason, here DARP is proposed.
State of the art classifiers split Alzheimer’s disease progression into a limited number of stages and use a comparatively small database. For the best treatment, it is desirable to have the highest resolution from the progression of the disease. This paper proposes a reliable deep convolutional neural network for the classification of six different Alzheimer’s disease stages based on Magnetic Resonance Imaging (MRI). The peculiarity of this paper is the introduction of a new, sixth, disease stage, and the large amount of data that has been taken into account. Additionally, not only the testing accuracy is analyzed, but also the robustness of the classifier to have feedback on how certain the neural network makes its predictions.