Sprechzeiten
Ich bin normalerweise Montags - Freitags von 10:00 - 16:00 in der Universität. Wenn ich nicht wegen einem Termin unterwegs bin, können Sie mich in meinem Büro O27-3210 antreffen. Alternativ können Sie einen Termin per Email mit mir vereinbaren.
Kommunikation
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Michael Wolf
- Bachelor of Science in Biotechnologie/Bioinformatik an der University of Applied Science in Mittweida
-> Bachelorarbeit „Die Analyse des Metatraskriptoms einer Biogasanlage und deren Darstellung auf einer Stoffwechselkarte“ - Bachelor of Science in Applied Bioscience an der University of the West of Scotland in Paisley (Schottland)
- Softwareentwickler/ DevOp in der Druckerei C.H.Beck in Nördlingen
- Master of Science in Software Engineering an der Universität Ulm
-> Masterarbeit „Combining Safety and Security Threat Modeling to Improve Automotive Penetration Testing“ in Kooperation mit der SCHUTZWERK GmbH. - Ein Semester an der Norwegian University of Science and Technology in Gjøvic (Norwegen)
- Seit Februar 2019 bin ich nun beim Institut für Verteilte Systeme als Wissenschaftlicher Mitarbeiter tätig.
Forschung
Mein Interesse gilt vielen Bereichen der Informatik, wie Software Development, IT Security, Privacy, Künstliche Intelligenz, ...
Momentan konzentriere ich mich auf Security for Connected Autonomous Cars.
Projekte
- BMBF gefördertes Projekt SecForCARs.
Lehre
Management der Seminare:
- Ausgewählte Themen in Verteilten Systemen - ATVS
- Forschungstrends in Verteilten Systemen - RTDS
- Privacy im Internet - PRIV
Betreuung der Übung:
Betreuung von Studenten:
Publikationen
2020
DOI: | 10.1109/vnc51378.2020.9318396 |
Abstract:
Cooperative Adaptive Cruise Control (CACC) is a typical example for cooperative maneuvers of connected, automated vehicles. Safe operation of any such vehicle highly depends on information emitted by the surrounding vehicles as it is processed by the vehicle's longitudinal controller. This opens an attack surface affecting vehicle safety. This paper studies how CACC controllers can be protected against such attacks to ensure the safety of the vehicle and its passengers. This raises the question of how to mitigate injection of false data into the controller by attacks and other forms of vehicle misbehavior. Based on a literature analysis, this paper defines a new categorization for mitigation strategies, discussing their individual strengths, weaknesses and their potential for attack mitigation. This categorization can be used to derive novel ideas for mitigations, for example, an approach with a parameter-dependent reaction of the controller based on a suspiciousness parameter signaled by the Misbehavior Detection System (MDS). Through a simulation study, we show that this approach improves safety and efficiency of the platoon under attack but also identify a fundamental trade-off between these two design goals.
DOI: | 10.1109/icc40277.2020.9149132 |
Abstract:
Cooperative Intelligent Transport Systems (C-ITS) is a new upcoming technology that aims at increasing road safety and reducing traffic accidents. C-ITS is based on peer-to-peer messages sent on the Vehicular Ad hoc NETwork (VANET). VANET messages are currently authenticated using digital keys from valid certificates. However, the authenticity of a message is not a guarantee of its correctness. Consequently, a misbehavior detection system is needed to ensure the correct use of the system by the certified vehicles. Although a large number of studies are aimed at solving this problem, the results of these studies are still difficult to compare, reproduce and validate. This is due to the lack of a common reference dataset. For this reason, the original VeReMi dataset was created. It is the first public misbehavior detection dataset allowing anyone to reproduce and compare different results. VeReMi is used in a number of studies and is currently the only dataset in its field. In this Paper, we extend the dataset by adding realistic a sensor error model, a new set of attacks and larger number of data points. Finally, we also provide benchmark detection metrics using a set of local detectors and a simple misbehavior detection mechanism.
2019
DOI: | 10.18725/OPARU-13062 |
Abstract:
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.
Abschlussarbeiten und Projekte
Individuelles Thema
Wenn Sie eine Idee für eine Abschlussarbeit oder Projekt aus meinem Interessengebiet haben, können Sie mich gerne für eine Betreuung kontaktieren.
Informationen
Für Details zu den Abschlussarbeiten und Projekten, oder weitere offene Themen von Kollegen, besuchen Sie bitte die entsprechende Seite unseres Instituts.
Offene Themen
Vergebene Themen
Abgeschlossene Themen
Seminare
Individuelles Seminarthema
Wenn Sie eine Idee für ein Seminarthema aus meinem Interessengebiet haben, können Sie mich gerne für eine Betreuung kontaktieren.
Informationen
Für Details zu den Seminaren besuchen Sie bitte die entsprechende Seite unseres Instituts.
Bachelorseminar ATVS und Masterseminar RTDS
Aktuelle Themen
- Password Managers (2021 SS)
Abgeschlossene Themen
- Time constraints of Security in CACC (2020 WS)
- Multi Agent Based Simulations (2020 WS)
- Internet of Things: A Security Perspective (2020 SS)
- Attacks on Platoons (2019 WS)
- Browser Privacy (2019 WS)
- Risk Evaluation Methodologies (2019 SS)
- IDS Algorithms (2019 SS)
Proseminar PRIV
Aktuelle Themen
- Privacy bei Messenger X (2021 SS)
- Privacy in Sozialen Netzwerken (2021 SS)
- Tor: The Onion Router (2021 SS)
Abgeschlossene Themen
- Kryptographische Grundlagen (2020 SS)
- Datenanonymisierung vs. Datennutzung (2020 SS)