Institut für Verteilte Systeme
Unser Institut beschäftigt sich mit Themen wie Skalierbarkeit, Zuverlässigkeit, Sicherheit und Datenschutz, Selbstorganisation und Beherrschbarkeit von Komplexität in Verteilten Systemen in einer Vielzahl von Einsatzszenarien wie Cloud-Computing oder Fahrzeug-Fahrzeug-Kommunikation.
In der Lehre decken wir das gesamte Spektrum von Rechnernetzen, über verteilte Systeme bis hin zu Sicherheit und Privacy-Schutz ab.
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Unsere letzten Publikationen
Towards automated smart mobile crowdsensing for tinnitus research
Proc. of the 32nd Int. Symp. on Comp.-Based Medical Sys. (CBMS)
Zusammenfassung: Tinnitus is a disorder that is not entirely understood, and many of its correlations are still unknown. On the other hand, smartphones became ubiquitous. Their modern versions provide high computational capabilities, reasonable battery size, and a bunch of embedded high-quality sensors, combined with an accepted user interface and an application ecosystem. For tinnitus, as for many other health problems, there are a number of apps trying to help patients, therapists, and researchers to get insights into personal characteristics but also into scientific correlations as such. In this paper, we present the first approach to an app in this context, called TinnituSense that does automatic sensing of related characteristics and enables correlations to the current condition of the patient by a combined participatory sensing, e.g., a questionnaire. For tinnitus, there is a strong hypothesis that weather conditions have some influence. Our proof-of-concept implementation records weather-related sensor data and correlates them to the standard Tinnitus Handicap Inventory (THI) questionnaire. Thus, TinnituSense enables therapists and researchers to collect evidence for unknown facts, as this is the first opportunity to correlate weather to patient conditions on a larger scale. Our concept as such is limited neither to tinnitus nor to built-in sensors, e.g., in the tinnitus domain, we are experimenting with mobile EEG sensors. TinnituSense is faced with several challenges of which we already solved principle architecture, sensor management, and energy consumption.
A Privacy-Aware V-Model for Software Development
Herausgeber: IEEE International Workshop on Privacy Engineering 2019,
Zusammenfassung: After the adoption of new data protection regulations, like GDPR, proper treatment of privacy throughout the system development lifecycle has become a must. In this paper, we discuss several aspects to more easily and effectively integrate privacy engineering in system development and how to bring the notion of privacy-by-design into practice. We propose the new W-model as a privacy-aware extension of the V-model frequently used in software engineering. One stage of the W-model deals with analyzing privacy in the system where privacy engineers conduct a privacy impact assessment in order to elicit privacy threats and to find a suitable countermeasure to remedy each threat. With respect to finding suitable countermeasures, we provide requirements the countermeasures need to meet in order to be selected. In addition, we introduce a cost function that assists privacy engineers in selecting the most suitable countermeasure. Furthermore, we point out several open issues that future work needs to address.
Poster: Towards A Reliable Privacy-Enhanced V-Model For Software Development
Herausgeber: IEEE Symposium on Security and Privacy 2019,
Zusammenfassung: In this poster, we propose solutions to the issue of incorporating privacy by design in the commonly used V-model for system development. In particular, we propose the W-model as an extension of the V-model, and further build on the W-model by proposing the novel σ-model which solves some limitations of the W-model.
Survey of Protocol Reverse Engineering Algorithms: Decomposition of Tools for Static Traffic AnalysisIEEE Communications Surveys and Tutorials, 21(1)
Zusammenfassung: Knowledge about a network protocol to understand the communication between entities is necessary for vulnerability research, penetration testing, malware analysis, network reconnaissance, and network modeling. Traffic analysis is one approach to infer a protocol. This approach shares common challenges, tasks, methods, and solutions. In this survey, we collect tools proposed by previous work in the research field of protocol reverse engineering by static traffic trace analysis. We dissect each tool to discern the individual mechanisms and the algorithms they are based on. Thereby, we categorize and contrast these mechanisms and algorithms that are used in static traffic trace analysis to discuss how successful they were applied in each case. We compared classification schemes for protocol reverse engineering to structure our discussion about the tools. We present and discuss an explicit process model for static traffic trace analysis revealing the common structure of the decomposed tools and frameworks from previous research. By discussions about the algorithms applied within each tool for each process task, we show relations between tools, methods, and the process. We validate our model by applying it to each of the tools, followed by an outline of the utility of protocol reverse engineering. Starting out from the process description, we deduce which solutions and algorithms have already been investigated and where challenges remain so that novel solutions need to be searched for in the future. Regarding the whole field of protocol reverse engineering, it is a prevalent problem that only very few implementations of tools and frameworks are publicly available.
Combining safety and security threat modeling to improve automotive penetration testing
Zusammenfassung: Newer technologies like connectivity and autonomy in the automotive sector increases the need for stronger security and for its evaluation penetration tests. In order to focus the tests first on the most critical possible vulnerabilities, threat modeling with a ranking of the risk level is mandatory. Because lives depend on the security of the vehicle, both safety and security aspects should be included into this threat model. Furthermore, the usage of a tool is required, which helps and automates some parts of the process, so the time effort is reduced and the acceptance of the methodology increased. Up to our knowledge no such holistic methodology exists, therefore we have created the CVSIL threat methodology. It combines the outcome of a Hazard Analysis and Risk Assessment (HARA) with results from using Microsofts’ Threat Modeling Tool 2016 and our own application, the TMTe4PT. With our proposed novel solution, after the faults have been mapped to the threats, the Collateral Damage Potential metric can be derived from the HARA, and so the CVSS overall score can be calculated and used as risk level. Additionally, we have introduced another score for the ranking, the Security-ASIL, which consists of elements from the security and safety analysis. For the evaluation, we have illustrated a hypothetical Adaptive Cruise Control (ACC) system and analyzed it with our model and tool. These findings were compared to those from expert interviews and the problems discussed. Based on our results, the CVSIL methodology in its current state does not provide a better distinction and therefore a better ranking between the threats violating the safety. The contribution of this thesis is the evaluation of existing threat methodologies, public threat modeling tools and our own CVSIL methodology. Furthermore we provide a hypothetical ACC system with system architecture and component definitions. For this system, the results of a shortened HARA and threat analysis are released. Additionally, our tool the TMTe4PT will be made open source.