Institut für Verteilte Systeme

Offene Abschlussarbeiten

Auf dieser Seite finden Sie Informationen zu aktuell von uns angebotenen Themen für Abschlussarbeiten. Informationen zu bereits laufenden oder fertiggestellten Arbeiten finden sich auf einer Unterseite. Beachten Sie, dass ausgeschriebene Arbeiten teilweise als Bachelor- und Masterarbeit oder auch als Projektarbeit ausgeschrieben sind. Je nachdem, was Studierende benötigen, wird in der Regel das Thema der gewählten Arbeit in Arbeitsumfang und Schwierigkeitsgrad angepasst.

Hinweis zur Sprache: Im Folgenden werden die verfügbaren Themen hauptsächlich auf Englisch aufgelistet. Bei der Bearbeitung eines Thema steht es Studierenden frei, sich entweder für Deutsch oder Englisch als Sprache für die Ausarbeitung zu entscheiden.

Aktuelle Ausschreibungen

„Efficient Updating of a Network-Protocol-Model with Message-Format Refinements,“ Bachelor's oder Masterarbeit, S. Kleber (Betreuung), F. Kargl (Prüfer), Institut of Distributed Systems, Ulm University, 2019 – Verfügbar.
Security assessments of networked systems require knowledge about the utilized communication protocol. For proprietary protocols without known specification and with only limited access to the end-points, the only source of information is the communication itself. To correctly conclude from the captured byte stream to message-formats, -types, and finally a protocol model, structure, message- and field-boundaries, data-type, and semantics need to be inferred.After an initial inference procedure, it is desirable to refine the existing protocol model. Additional information gained by recorded network traffic needs to be incorporated by recognizing the appropriate parts of the model. The modeled knowledge is to be extended depending on the applicable information inferable from the new trace.
„Test-Case-Generation Strategies for Network-Protocol-Model Refinements,“ Bachelor's oder Masterarbeit, S. Kleber (Betreuung), F. Kargl (Prüfer), Institut of Distributed Systems, Ulm University, 2019 – Verfügbar.
Security assessments of networked systems require knowledge about the utilized communication protocol. For proprietary protocols without known specification and with only limited access to the end-points, the only source of information is the communication itself. To correctly conclude from the captured byte stream to message-formats, -types, and finally a protocol model, structure, message- and field-boundaries, data-type, and semantics need to be inferred.After an initial inference procedure, it is desirable to refine the existing protocol model. Actively probing an entity for the validity of message syntaxes allows to targetedly enhance the knowledge about the protocol. To do this efficiently a smart method of automatically generating test-cases depending on the current protocol model needs to be developed.
„Machine Learning on Encrypted Data,“ Bachelor Thesis, Master Thesis, Projektarbeitarbeit, M. Matousek (Betreuung), F. Kargl (Prüfer), Inst. of Distr. Sys., Ulm Univ., 2018 – Verfügbar.
Encryption is one of the most reliable techniques for protecting information. However, once data is encrypted, using it becomes very difficult. Goal of this thesis or project, is to explore how Machine Learning algorithms can be designed to be able to deal with encrypted data. Firstly, a survey of existing mechanisms should be conducted. In a second part, algorithms will be comparatively implemented, or own encryption mechanisms introduced.

Themen nach Abschluss

Bachelor-Arbeiten

„Efficient Updating of a Network-Protocol-Model with Message-Format Refinements,“ Bachelor's oder Masterarbeit, S. Kleber (Betreuung), F. Kargl (Prüfer), Institut of Distributed Systems, Ulm University, 2019 – Verfügbar.
Security assessments of networked systems require knowledge about the utilized communication protocol. For proprietary protocols without known specification and with only limited access to the end-points, the only source of information is the communication itself. To correctly conclude from the captured byte stream to message-formats, -types, and finally a protocol model, structure, message- and field-boundaries, data-type, and semantics need to be inferred.After an initial inference procedure, it is desirable to refine the existing protocol model. Additional information gained by recorded network traffic needs to be incorporated by recognizing the appropriate parts of the model. The modeled knowledge is to be extended depending on the applicable information inferable from the new trace.
„Test-Case-Generation Strategies for Network-Protocol-Model Refinements,“ Bachelor's oder Masterarbeit, S. Kleber (Betreuung), F. Kargl (Prüfer), Institut of Distributed Systems, Ulm University, 2019 – Verfügbar.
Security assessments of networked systems require knowledge about the utilized communication protocol. For proprietary protocols without known specification and with only limited access to the end-points, the only source of information is the communication itself. To correctly conclude from the captured byte stream to message-formats, -types, and finally a protocol model, structure, message- and field-boundaries, data-type, and semantics need to be inferred.After an initial inference procedure, it is desirable to refine the existing protocol model. Actively probing an entity for the validity of message syntaxes allows to targetedly enhance the knowledge about the protocol. To do this efficiently a smart method of automatically generating test-cases depending on the current protocol model needs to be developed.
„Machine Learning on Encrypted Data,“ Bachelor Thesis, Master Thesis, Projektarbeitarbeit, M. Matousek (Betreuung), F. Kargl (Prüfer), Inst. of Distr. Sys., Ulm Univ., 2018 – Verfügbar.
Encryption is one of the most reliable techniques for protecting information. However, once data is encrypted, using it becomes very difficult. Goal of this thesis or project, is to explore how Machine Learning algorithms can be designed to be able to deal with encrypted data. Firstly, a survey of existing mechanisms should be conducted. In a second part, algorithms will be comparatively implemented, or own encryption mechanisms introduced.

Master-Arbeiten

„Efficient Updating of a Network-Protocol-Model with Message-Format Refinements,“ Bachelor's oder Masterarbeit, S. Kleber (Betreuung), F. Kargl (Prüfer), Institut of Distributed Systems, Ulm University, 2019 – Verfügbar.
Security assessments of networked systems require knowledge about the utilized communication protocol. For proprietary protocols without known specification and with only limited access to the end-points, the only source of information is the communication itself. To correctly conclude from the captured byte stream to message-formats, -types, and finally a protocol model, structure, message- and field-boundaries, data-type, and semantics need to be inferred.After an initial inference procedure, it is desirable to refine the existing protocol model. Additional information gained by recorded network traffic needs to be incorporated by recognizing the appropriate parts of the model. The modeled knowledge is to be extended depending on the applicable information inferable from the new trace.
„Test-Case-Generation Strategies for Network-Protocol-Model Refinements,“ Bachelor's oder Masterarbeit, S. Kleber (Betreuung), F. Kargl (Prüfer), Institut of Distributed Systems, Ulm University, 2019 – Verfügbar.
Security assessments of networked systems require knowledge about the utilized communication protocol. For proprietary protocols without known specification and with only limited access to the end-points, the only source of information is the communication itself. To correctly conclude from the captured byte stream to message-formats, -types, and finally a protocol model, structure, message- and field-boundaries, data-type, and semantics need to be inferred.After an initial inference procedure, it is desirable to refine the existing protocol model. Actively probing an entity for the validity of message syntaxes allows to targetedly enhance the knowledge about the protocol. To do this efficiently a smart method of automatically generating test-cases depending on the current protocol model needs to be developed.
„Machine Learning on Encrypted Data,“ Bachelor Thesis, Master Thesis, Projektarbeitarbeit, M. Matousek (Betreuung), F. Kargl (Prüfer), Inst. of Distr. Sys., Ulm Univ., 2018 – Verfügbar.
Encryption is one of the most reliable techniques for protecting information. However, once data is encrypted, using it becomes very difficult. Goal of this thesis or project, is to explore how Machine Learning algorithms can be designed to be able to deal with encrypted data. Firstly, a survey of existing mechanisms should be conducted. In a second part, algorithms will be comparatively implemented, or own encryption mechanisms introduced.

Themen nach Schwerpunkt

Netzwerke

„Efficient Updating of a Network-Protocol-Model with Message-Format Refinements,“ Bachelor's oder Masterarbeit, S. Kleber (Betreuung), F. Kargl (Prüfer), Institut of Distributed Systems, Ulm University, 2019 – Verfügbar.
Security assessments of networked systems require knowledge about the utilized communication protocol. For proprietary protocols without known specification and with only limited access to the end-points, the only source of information is the communication itself. To correctly conclude from the captured byte stream to message-formats, -types, and finally a protocol model, structure, message- and field-boundaries, data-type, and semantics need to be inferred.After an initial inference procedure, it is desirable to refine the existing protocol model. Additional information gained by recorded network traffic needs to be incorporated by recognizing the appropriate parts of the model. The modeled knowledge is to be extended depending on the applicable information inferable from the new trace.
„Realisierung von spieltheoretischer Peer-to-Peer Netzwerkerzeugung II,“ D. Mödinger (Betreuung), F. J. Hauck (Prüfer), Inst. of Distr. Sys., Ulm Univ., 2019 – Verfügbar.
Die Topologie von Peer-to-Peer-Netzen spielt für viele darauf aufbauende Protokolle eine zentrale Bedeutung. So bestimmt der Netzwerkdurchmesser beispielsweise, wie schnell alle Teilnehmer Broadcastnachrichten erhalten können. Zudem agieren Teilnehmer in einem Peer-to-Peer-Netzwerk üblicherweise so, dass sie ihre ei-gene Situation verbessern. Basierend darauf lassen sich die Hand-lungen der Teilnehmer spieltheoretisch modellieren. Ziel dieser Arbeit ist es, aufbauend auf Ergebnisse einers vorherigen Projekts, ein gegebenes spieltheoretisches Modell in ein Protokoll umzusetzen, das jeder Spieler bzw. Teilnehmer befolgt. Hierfür soll die gegebene Simulation erweitert werden. Dieses Projekt wird in Kooperation zwischen den Instituten für Theoretische Informatik und Verteilte Systeme durchgeführt und gemeinsam betreut.
„Test-Case-Generation Strategies for Network-Protocol-Model Refinements,“ Bachelor's oder Masterarbeit, S. Kleber (Betreuung), F. Kargl (Prüfer), Institut of Distributed Systems, Ulm University, 2019 – Verfügbar.
Security assessments of networked systems require knowledge about the utilized communication protocol. For proprietary protocols without known specification and with only limited access to the end-points, the only source of information is the communication itself. To correctly conclude from the captured byte stream to message-formats, -types, and finally a protocol model, structure, message- and field-boundaries, data-type, and semantics need to be inferred.After an initial inference procedure, it is desirable to refine the existing protocol model. Actively probing an entity for the validity of message syntaxes allows to targetedly enhance the knowledge about the protocol. To do this efficiently a smart method of automatically generating test-cases depending on the current protocol model needs to be developed.

Mobile Systeme

Distributed Computing

Privacy

IT-Sicherheit

Fehlertoleranz

Cloud Computing

„Machine Learning on Encrypted Data,“ Bachelor Thesis, Master Thesis, Projektarbeitarbeit, M. Matousek (Betreuung), F. Kargl (Prüfer), Inst. of Distr. Sys., Ulm Univ., 2018 – Verfügbar.
Encryption is one of the most reliable techniques for protecting information. However, once data is encrypted, using it becomes very difficult. Goal of this thesis or project, is to explore how Machine Learning algorithms can be designed to be able to deal with encrypted data. Firstly, a survey of existing mechanisms should be conducted. In a second part, algorithms will be comparatively implemented, or own encryption mechanisms introduced.

Multimediakommunikation

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