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Fault Handling Approaches on Dual-Core Microcontrollers in Safety-Critical Automotive Applications
(2009)
Die hier vorliegende Diplomarbeit befasst sich mit dem Thema "Realisierung und Implementierung einer zentralen, funkgestützten Steuerung der Rollladen eines Einfamilienhauses". Die entworfene Schaltung ist kompatibel zu einem bestehenden Funkschaltsystem für Steckdosen und Dimmer. Ein weiterer Zielpunkt dieser Diplomarbeit war, dass die neue Schaltung günstiger herzustellen ist, als schon existierende Systeme. Die Funktionalität eine Rolllade per Taster oder durch eine Funkfernbedienung, auf 433MHz Basis, zu bedienen bzw. zu steuern ist auch gegeben. Durch eine Verkleinerung der Platine bzw. eine Optimierung der Programmierung ist eine Verbesserung der Schaltung möglich. Weitere Funktionen können durch Ergänzung der Hard- und Software hinzugefügt werden.
ALPACA: Application Layer Protocol Confusion - Analyzing and Mitigating Cracks in TLS Authentication
(2021)
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.
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.
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.
Body energy harvesting for WSN. State of art and examples
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.
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.
About Nuclear Resonant Reaction Analysis for Hydrogen Investigations in Amorphous Silicon Layers
(2015)
Capacitance-voltage spectroscopy and analysis of dielectric intrinsic amorphous silicon thin films
(2016)
Reviewing Cyber Security Research of Implantable Medical Rhythm Devices regarding Patients’ Risk
(2020)
Introduction: The recent publication of several critical cyber security issues in cardiac implantable devices and the resulting press coverage upsets affected users and their trust in medical device producers. Reviewing the published security vulnerabilities regarding networked medical devices, it raises the question, if the reporting media, the responsible security researchers, and the producers handle security vulnerabilities appropriately. Are the media reports of security vulnerabilities in medical devices meaningful in a way that patients can assess their respective risk for an attack via the security vulnerability? The collaboration between IT-security experts and clinicians aims at reviewing published security vulnerabilities of rhythm devices, and evaluate overall patients risks.
Methodology: We performed a literature review on security vulnerabilities in implantable medical devices with a focus on cardiac devices. We analyzed (Fig. 1) the (1) requirements for an attacker and the (2) technical feasibility and clustered them in three different scenarios: The first scenario requires that the attacker physically approaches a victim with a programming device. The second scenario requires proximity to the victim, e.g., within a few meters. The third and strongest attacker scenario is a remote attack that doesn’t require any physical proximity to the victim. We then compare the attacker scenarios and (3) the overall patients’ risks with the press coverage (overhyped, adequate, underhyped). (4) The resulting overall patients’ risk was rated by clinicians (security vulnerability of patients’ data, dangerous programming possible).
Results: Out of the three analyzed incidents, we found one to be underhyped, one to be overhyped, and one was appropriate compared to the medial coverage (Fig. 2). The most occurring technical issues were based on the absence of basic security primitives. The patient damage for all of the analyzed incidents was fatal in the worst-case scenario. Further, the patient damage and the overall patient risks are disjunct due to the missing capability of performing large scale attacks.
Conclusion: The resulting overall patients’ risks may not adequately reflect the patient damage in the considered cases. Often, the overall patient risk is not as severe as the necessary attacker capabilities are high and it would require strongly motivated attackers to perform the attack. Therefore, most of the reviewed cases are considered with a smaller overall patient risk than implied by press reports. Reviewing the ongoing IT-Security trends regarding implantable medical devices shows an increasing focus on researching in the field of medical device security. Therefore, further findings in the near future are to be expected. To deal with this fact in a responsible way, proper proactive knowledge management is mandatory. We recommend medical staff to critically reflect reports in mass media due to possible sensationalism. Therefore, we propose a joint approach in combining the technical expertise of cyber security experts with clinical aspects of medical experts, to ensure a solid understanding of a newly published vulnerability. The combination of both communities promises to result in better predictions for patients’ risks from security vulnerabilities in implanted cardiac devices.
Wireless Sensor Networks
(2013)
Embedded Systems
(2013)
Wireless Sensor
(2013)
Asynchronous Circuit Design Based on the RTBT Monostable-Bistable-Logic-Transiton-Element (MOBILE)
(2002)
Die Beiträge, der Konferenz:
• Nanotechnologie –Von Wunder-Materialien und solchen die es werden wollen
• Mikrotechnik –to improve the qualityof live
• Quantum Sensing for Industrial Applications
• Geordnete Defekte in Graphit: Ein Fahrplan in Richtung Raumtemperatur Supraleitung
• Funktionale mikro-und nanostrukturierte Folien als Bestandteil hochintegrierter Systeme
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.
Cache Attacks on Intel SGX
(2017)
This work describes the setup of an ultrawideband (UWB)
realtime localization system (RTLS) for tracking of particles.We describe
how the RTLS obtains distances and positions through radio waves and
the setup and evaluation of a real world system is stated in detail. In
the proposed system the particles track a subtrates surface
ow inside a
biogas plant for verication of agitation processes.
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.