Elektrotechnik und Informatik (ETI)
Refine
Year
Publication Type
- Part of a Book (119)
- Lecture (83)
- Article (68)
- Conference Proceeding (42)
- Book (20)
- Participation in a Norm (DIN, RFC etc.) (13)
- Master's Thesis (4)
- Course Material (3)
- Report (2)
- Bachelor Thesis (1)
Language
- English (197)
- German (131)
- Multiple languages (27)
Keywords
- Photovoltaik, Solarstrom, Speicher (5)
- Cyber Security (4)
- Elektrotechnik (3)
- Photovoltaik (3)
- QUIC (3)
- Outdoor-EL (2)
- Photovoltaics (2)
- Solarstrom (2)
- Transport Protocol (2)
- Ack Ratio (1)
KIM: Kaos In der Medizin
(2024)
Die sichere E-Mail-Infrastruktur für Ärzt*innen, Apotheker*innen, Krankenversicherungen und Kliniken in Deutschland, KIM - Kommunikation im Gesundheitswesen - ist mit über 200 Millionen E-Mails in den vergangenen zwei Jahren eine der am meisten genutzten Anwendungen in der Telematikinfrastruktur. Mit dem Ausgeben von S/MIME-Zertifikaten für alle medizinische Beteiligten in Deutschland verspricht KIM sichere Ende-zu-Ende-Verschlüsselung von E-Mails zwischen Heilberufler*innen in ganz Deutschland.
In diesem Paper analysieren wir die KIM-Spezifikation sowie eine beispielhafte KIM-Installation in einer deutschen Zahnarztpraxis. Wir zeigen, dass KIM kryptografisch ein sehr hohes Sicherheitslevel erfüllt, doch in der Verarbeitung der E-Mails bei den Clients eine schwerwiegende Sicherheitslücke besteht. Weiterhin zeigen wir zwei Sicherheitslücken in dem KIM-Verarbeitungsmodul eines großen deutschen Unternehmens für medizinische Software. Diese Defizite zeigen außerdem Mängel in dem verpflichtenden Zulassungsprozess der KIM-Komponenten auf.
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.
A communication over an Internet Protocol (IP) based network fails if an endpoint sends packets that are too big to reach their destination and if the sender is unable to detect that. The node on the path that drops these packets should respond with a Packet Too Big (PTB) message. However, multiple scenarios exist in which the sender will not receive a PTB message. Even if it does, it refrains from using the information in case it suspects that a potential attacker forged the message. In particular, we are not aware of any implementation of the secure transport protocol QUIC (e.g., used by HTTP/3) that processes PTB messages. In this paper, we present a novel parameterizable PTB detection algorithm for reliable transport protocols that does not depend on PTB messages. We further describe how to integrate our algorithm into QUIC, present results from an evaluation using the algorithm within a QUIC simulation model and, based on these results, suggest concrete parameter values.
Durchgängige Digitalisierung industrieller Abläufe am Beispiel der Modellfabrik der FH Münster
(2023)
Die Modellfabrik der FH Münster erlaubt durch den Umfang und die Komplexität der enthaltenen Automatisierungsaufgaben sowie einen Aufbau aus industriellen Komponenten eine praxisnahe Lehre im Bereich aktueller Anlagenautomatisierung und darüber hinausgehenden Funktionen im Sinne einer durchgängigen Digitalisierung. Die verwendete Unterscheidung der durchgängigen Digitalisierung in horizontale und vertikale Verknüpfungen wird veranschaulicht. Aufbauend auf Erfahrungen mit der Vorgängeranlage werden Neuerungen der 2021 aufgebauten neuen Modellfabrik vorgestellt. Neuerungen umfassen insbesondere die Modularisierung der Anlage, das umgesetzte Sicherheitskonzept, einen Webshop mit Onlinekonfigurator, eine Webvisualiserung des Anlagenzustandes inklusive der Energieverbräuche, sowie Möglichkeiten zur virtuellen Inbetriebnahme. Weiterhin wird das aktuelle Konzept zur Erweiterung der horizontalen digitalen Durchgängigkeit mittels der Einbindung eines autonomen mobilen Roboters in die Modellfabrik vorgestellt.
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
Quantum magnetometry based on optically detected magnetic resonance (ODMR) of nitrogen vacancy centers in nano- or micro-diamonds is a promising technology for precise magnetic-field sensors. Here, we propose a new, low-cost and stand-alone sensor setup that employs machine learning on an embedded device, so-called edge machine learning. We train an artificial neural network with data acquired from a continuous-wave ODMR setup and subsequently use this pre-trained network on the sensor device to deduce the magnitude of the magnetic field from recorded ODMR spectra. In our proposed sensor setup, a low-cost and low-power ESP32 microcontroller development board is employed to control data recording and perform inference of the network. In a proof-of-concept study, we show that the setup is capable of measuring magnetic fields with high precision and has the potential to enable robust and accessible sensor applications with a wide measuring range.
S/MIME and OpenPGP use cryptographic constructions repeatedly shown to be vulnerable to format oracle attacks in protocols like TLS, SSH, or IKE. However, format oracle attacks in the End-to-End Encryption (E2EE) email setting are considered impractical as victims would need to open many attacker-modified emails and communicate the decryption result to the attacker. But is this really the case?
In this paper, we survey how an attacker may remotely learn the decryption state in email E2EE. We analyze the interplay of MIME and IMAP and describe side-channels emerging from network patterns that leak the decryption status in Mail User Agents (MUAs). Concretely, we introduce specific MIME trees that produce decryption-dependent net work patterns when opened in a victim’s email client.
We survey 19 OpenPGP- and S/MIME-enabled email clients and four cryptographic libraries and uncover a side-channel leaking the decryption status of S/MIME messages in one client. Further, we discuss why the exploitation in the other clients is impractical and show that it is due to missing feature support and implementation quirks. These unintended defenses create an unfortunate conflict between usability and security. We present more rigid countermeasures for MUA developers and the standards to prevent exploitation.
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.
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.
Medizinische Einrichtungen waren in den letzten Jahren immer wieder von Cyber-Angriffen betroffen. Auch wenn sich diese Angriffe derzeit auf die Office-IT-Infrastruktur der Einrichtungen konzentrieren, existiert mit medizinischen Systemen und Kommunikationsprotokollen eine weitere wenig beachtete Angriffsoberfläche.
In diesem Beitrag analysieren wir die weit verbreiteten medizintechnischen Kommunikations-Protokolle DICOM und HL7 sowie Protokoll-Implementierungen auf ihre IT-Sicherheit. Dafür präsentieren wir die Ergebnisse der Sicherheitsanalyse der DICOM- und HL7-Standards, einen Fuzzer “MedFUZZ” für diese Protokolle sowie einen Schwachstellenscanner “MedVAS”, der Schwachstellen in medizintechnischen Produktivumgebungen auffinden kann.
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.
A data sender in an IP based network is only capable to efficiently use a network path if it knows the packet size limit of the path, i.e., the Path Maximum Transmission Unit (PMTU). The IETF recently specified a PMTU discovery framework for transport protocols like QUIC. This paper complements this specification by presenting a search algorithm. In addition, it defines several metrics and shows results of analyses for the algorithm with various PMTU candidate sequences using these metrics. We integrated the PMTU discovery with our algorithm into a QUIC simulation model. This paper describes the integration and presents measurements obtained by simulations.
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.
Piston pumps play a key role in factory automation and their availability is very critical for the smooth running of production processes. Modern installations, such as production plants and machines, are becoming increasingly complex. Therefore, the probability of a complete system failure due to a single critical component also increases. Maintenance processes with intelligent devices are therefore very important to achieve maximum economic efficiency and safety. Periodic or continuous monitoring of system components provides key information about the current physical state of the system, enabling early detection of emerging failures. Knowledge of future failures makes it possible to move from the concept of preventive maintenance to intelligent predictive maintenance. In this way, consequential damage and complete system failure can be avoided, maximizing system availability and safety. This paper reflects the development and implementation of a neural network system for abnormal state prediction of piston pumps. After a short introduction into piston pumps and their potential abnormal states, statistical and periodical analysis are presented. Then the design and implementation of suitable neural networks are discussed. Finally, a conclusion is drawn and the observed accuracies as well as potential next steps are discussed.
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.
Due to the increasing connectivity of modern vehicles, collected data is no longer only stored in the vehicle itself but also transmitted to car manufacturers and vehicle assistant apps. This development opens up new possibilities for digital forensics in criminal investigations involving modern vehicles. This paper deals with the digital forensic analysis of vehicle assistant apps of eight car manufacturers. We reconstruct the driver’s activities based on the data stored on the smartphones and in the manufacturer’s backend.
For this purpose, data of the Android and iOS apps of the car manufacturers Audi, BMW, Ford, Mercedes, Opel, Seat, Tesla, and Volkswagen were extracted from the smartphone and examined using digital forensic methods following forensics guidelines. Additionally, manufacturer data was retrieved using Subject Access Requests. Using the extensive data gathered, we reconstruct trips and refueling processes, determine parking positions and duration, and track the locking and unlocking of the vehicle.
Our findings show that the digital forensic investigation of smartphone applications is a useful addition to vehicle forensics and should therefore be taken into account in the strategic preparation of future digital forensic investigations.
Modern implantable cardiologic devices communicate via radio frequency techniques and nearby gateways to a backend server on the internet. Those implanted devices, gateways, and servers form an ecosystem of proprietary hardware and protocols that process sensitive medical data and is often vital for patients’ health.
This paper analyzes the security of this Ecosystem, from technical gateway aspects, via the programmer, to configure the implanted device, up to the processing of personal medical data from large cardiological device producers. Based on a real-world attacker model, we evaluated different devices and found several severe vulnerabilities. Furthermore, we could purchase a fully functional programmer for implantable cardiological devices, allowing us to re-program such devices or even induce electric shocks on untampered implanted devices.
Additionally, we sent several Art. 15 and Art. 20 GDPR inquiries to manufacturers of implantable cardiologic devices, revealing non-conforming processes and a lack of awareness about patients’ rights and companies’ obligations. This, and the fact that many vulnerabilities are still to be found after many vulnerability disclosures in recent years, present a worrying security state of the whole ecosystem.