|Titel:||Forschungstrends in Verteilten Systemen|
|Englischer Titel:||Research Trends in Distributed Systems|
|Kürzel / Nr. / Modulnr.:||RTDS / CS5900.114 / 71926|
|SWS / LP:||2S / 4LP|
|Dozent:||Prof. Dr. Frank Kargl, Prof. Dr.-Ing. Franz J. Hauck|
|Betreuer:||Ala'a Al-Momani, Felix Engelmann, Benjamin Erb, Eugen Frasch, Gerhard Habiger, Stephan Kleber, Henning Kopp, Dominik Lang, Thomas Lukaseder, Matthias Matousek, Dominik Meißner, David Mödinger, Rens van der Heijden|
Räume und Daten werden noch bekannt gegeben
|Lernplattform:||Kursmaterialien finden Sie im Moodle-Kurs. Sie werden dem Kurs automatisch hinzugefügt, sobald Sie eines unserer Seminare besuchen.|
|Themenvergabe:||Die Themenvergabe erfolgt über die zentrale Seminarthemen-Vergabe-Plattform.|
|Sprache:||Alle Themen sollen im Masterseminar nur in englischer Sprache bearbeitet werden.|
• frei ✘ belegt
✘ Trends in Privacy Engineering – English only
Privacy-by-Design (PbD) has been emerged rapidly especially after the adoption of the new EU General Data Protection Regulation (GDPR) in 2016. This raise the need for a systematic approach to convert the requirement taken from such regulations to be in the form of engineered and technical requirements. In this seminar, you will survey the available methodologies for this engineering process considering both risk-based analysis approaches and goal-oriented approaches. This will help you to gain valuable insights in the field of privacy engineering and PbD.
✘ Recent Advances in Autonomous Driving – English only
Autonomous Driving as well as other AI-based applications have the potential to shape our future. The development of advanced and efficient machine learning algorithms made Autonomous Driving possible nowadays. In this seminar, you will address autonomous driving from both points of view: the theoretical (based on the literature) as well as the practical one. In particular, you will survey and compare the existing work in this field and try to answer the question which machine learning technique performs best in Autonomous Driving. Moreover, you need to address (based on the literature) the question of how V2X communication can enhance the autonomous driving experience.
✘ Deep Learning vs. Reinforcement Learning: When to Use Which? – English only
Deep Learning (DL) allowed Google to master the game of Go a decade earlier than expected through building an AI machine that is capable of beating expert players at the mentioned game. On the other hand, Reinforcement Learning (RL) allows, experimentally, AI machines to figure out things that no programmer could teach them and it is considered one of the top ten breakthrough technologies in 2017 according to the MIT technology review. In this seminar, you will investigate both learning techniques while addressing what benefits each one brings over the other. In addition, in what applications each one fits the best. Moreover, you need to address the best practices in these emerging technologies. By this, you also need to investigate real-world DL- and RL-based applications and try to figure out why this has been used and not the other. Previous knowledge in ML/DL/RL/NN/AI is preferred and it will help you progress faster in this seminar.
✘ Architectures for Data-intensive Applications – English only
Data-intensive applications require reliability, scalability, and maintainability. This seminar topic addresses system architectures that enable such applications and introduces the relevant concepts and mechanisms.
✘ π-calculus – English only
As a process calculus the p-calculus describes the movement of a piece of data in exactly the same way as the tranfer of a message. Thus the p-calculus is used to define concurrent computations whose network configuration may change during the computation. The goal of this seminar is to look at motivation, theory and expressiveness of pi-calculus.
✘ TensorFlow – English only
Developed by Google TensorFlow is an open source software library for machine learning. It uses data flow graphs for numerical computation. The flexible architecture allows to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. The goal of this seminar is to give introduction to TensorFlow, its usecases and deeper characteristics.
Note: basic knowledge in Python is recommended.
✘ Algorithms for Real-Time Scheduling on Multiprocessor – English only
Nowadays there exists a great number of research work focused on the study of real-time scheduling in one processor. However, the research area of real-time scheduling on multiprocessor systems is quite new. The goal of this seminar is to give an overview of methods for real-time scheduling on multiprocessor and their known algorithms.
✘ Modern Encryption for File Sharing – English only
In modern applications we value confidentiality of files we sent (e.g. pictures, bank statements, contracts). Simple encryption will force us to share the password with everyone. Some systems will allow us to specify possible recipients with public keys. The goal of this seminar is to research these systems and provide an introduction to a concrete and secure shareable encryption scheme.
✘ Temporal Logic of Actions: model checking concurrent distributed systems – English only
Due to their diversity and complexity, distributed systems often exhibit indeterministic behaviour. This makes it very hard to correctly design new systems, since errors may only manifest themselves rarely and under specific circumstances, which are difficult to test for. Mathematically modeling such systems allows to formally test their behaviour and exhaustively check every possible state they can ever be in, making it (theoretically) impossible for a system to fail due to design flaws. One tool to model concurrent distributed systems is Lamport's TLA+. The goal of this seminar is to give an introduction to TLA+ and its current state, and to provide an example of a real world application of TLA+.
✘ Misbehavior Detection in Vehicular Networks – English only
One approach to improve road safety and efficiency in the future is by allowing vehicles to communicate and warn or plan their routes. This is realized through vehicular ad-hoc networks. These networks improve safety and efficiency by sending messages to, for example, inform vehicles in a particular area that a traffic jam is ahead of them. For the correct and safe operation of applications, it is essential that the information sent by other vehicles can be trusted or verified. In this seminar paper, you will discuss one or two new approaches to detect misbehavior of vehicles in these networks, and put these into the context of existing work.
✘ Alignment-free Protocol Message Format Reverse Engineering – English only
Understanding the communication of networked systems without knowing the protocol specification can be achieved by the reverse engineering of the network traffic. Examples for use cases of this approach are the analysis of botnets and vulnerability detection in network protocol implementations. Several methods to infer the protocol message format use the Needleman-Wunsch-algorithm-based progressive multiple sequence alignment. Instead, also alignment-free methods to find structure in byte sequences are available. An especially interesting example is the Leimeister et al. alignment-free method.
The goal of this seminar topic is to identify commonalities and differences between alignment and alignment-free algorithms with focus on applicability to infer message formats of protocols and to discuss their respective strengths and weaknesses.
✘ Cryptography Engineering – English only
Every day we rely on the security of applied cryptography (e.g. security protocols) to protect our data. This application of cryptography in real world solutions is difficult and prone to errors; one mistake can compromise the entire security.
✘ Policy Checking of Network Topologies – English only
Network policies are rules that define how a network needs to be set up. They contain for instance demands concerning the reachability of certain network devices or filter rules for firewalls. Tools like netplumber exist to help in the verification process whether a network topology complies with these policies. Goal of this seminar is to analyze how these tools work and which policies can or cannot be analyzed by these tools.
✘ Analysis of Distributed Denial of Service Attacks – English only
Distributed Denial of Service Attacks are a common problem in networks all over the world. They are hard to defend against as they affect services that usually are accessible to the public and exploit usual, standard conform behaviour. There are many different kinds of attacks. From the usual flooding attacks over slow HTTP attacks to reflective attacks, there are many ways a system can be taken down. Attackers mimic the behaviour of legitimate clients and thus make it hard to be identified as perpetrators. This seminar shall analyse the different kinds of attacks, how attackers can be identified, and how attacks can be mitigated.
✘ Machine Learning Privacy – English only
Machine Learning has a number of very useful applications and offers great benefits. Machine learning algorithms can be used for recommendation systems, data analysis, or security applications. However, while machine learning can provide useful predictions and analysis, there are also privacy concerns. The aim of this seminar is to identify privacy issues, and survey possible solutions.
✘ Networking in Online Multiplayer Games – English only
Online multiplayer games and other distributed real-time applications face various challenges when it comes to networking and communication. Communication properties of such applications are quite different in contrast to traditional networking applications. The goal of this seminar is to give an overview of the challenges in network games and best practices how these challenges can be addressed.
✘ Machine Learning on Event Streams – English only
Machine Learning approaches and algorithms can be utilized to analyze event streams and time-series data and forecast events. This has shown very promising results in the domain of weather forecasting and stock market prediction. However, current research is not limited to these domains. The goal of this seminar is to give an overview of current approaches, possibilities, and limitations of machine learning on event streams and time-series.
Special Interdisciplinary Research Seminar on Digitalization of Law through Blockchains and Smart Contracts
The following topics are part of an interdisciplinary research seminar jointly organized with the Institute of Accounting and Auditing and researchers from University of Heidelberg. Talks are going to be presented at a workshop planned for 2nd or 3rd of February 2018 at Kloster Roggenburg near Ulm. Attending this workshop is required. Travel costs will be covered by the organizers. Except for the final presentation, the special seminar follows the same schedule as the other seminar topics.
✘ Ethereum – English only
This talk will introduce the Ethereum system with a focus on the Smart Contracts mechanisms. It should particularly illustrate how to develop smart contracts in the Solidity programming language and how those smart contracts are executed in Ethereum.
✘ Bitcoin – English only
Bitcoin is the first fully decentralized digital currency. The individual Bitcoins are created and managed by a distributed Peer-2-Peer network. The work should provide an overview over the Bitcoin ecosystem and extend the focus to the general concepts of Blockchain-based technologies.
✘ How to undo transactions in Blockchain-based Systems? – English only
What concepts can you apply, if a (national) court rules that a transaction was illegal? As illustrated by e.g. the DAO, smart contracts and digital currencies based on blockchains face substantial problems in case of fraud, as there is no real jurisdictional oversight possible. Once in the ledger, transactions cannot be removed retroactively. This talk should investigate such fraud cases and which technical options one has to implement jurisdictional decisions.
Beschreibung und allgemeine Angaben, Modulbeschreibung
|Einordnung in die Studiengänge:||Informatik, M.Sc.: Seminar |
Medieninformatik, M.Sc.: Seminar
Software-Engineering, M.Sc.: Seminar
Informatik, Dipl.: Hauptseminar
Medieninformatik, Dipl.: Hauptseminar
(siehe auch unsere Hinweise zu Seminaren)
|Lehr- und Lernformen:||Forschungstrends in Verteilten Systemen, 2S, 4LP|
|Verantwortlich:||Prof. Dr. Frank Kargl|
|Unterrichtssprache:||Deutsch, Präsentationen in Deutsch oder Englisch (bevorzugt)|
|Turnus / Dauer:||jedes Semester / ein volles Semester|
|Voraussetzungen (inhaltlich):||Grundlagen in Rechnernetzen, Proseminar, Grundlagen Verteilter Systeme (empfohlen)|
|Grundlage für (inhaltlich):||-|
|Lernergebnisse:||Das Forschungsseminar verfolgt zwei Ziele. Einerseits sollen Studierende umfassend in wissenschaftlichen Arbeitstechniken geschult werden, in dem ein (vereinfachter und verkürzter) Forschungszyklus bestehend aus Problemanalyse, Literaturrecherche, eigenem Beitrag, Publikation und Präsentation vor Fachpublikum durchlaufen wird. Andererseits dient die Auseinandersetzung mit einem aktuellen Forschungsthema aus dem Bereich der Verteilten Systeme und dient so der Vertiefung und eventuellen Vorbereitung auf ein Thema einer Masterarbeit.|
|Inhalt:||Zu Beginn des Seminars werden Themen des wissenschaftlichen Arbeitens (z.B. Literaturrecherche, Schreiben einer Publikation, Präsentationstechniken) eingeführt, um den Studenten eine methodische Hilfestellung zu geben. Die Erstellung der eigentlichen Ausarbeitung und Präsentation erfolgt in individueller Betreuung. Die Ergebnisse werden in einer Abschlusspräsentation vorgestellt.|
|Literatur:||Wird je nach Thema zu Beginn der Veranstaltung bekannt gegeben.|
|Bewertungsmethode:||Leistungsnachweis über erfolgreiche Teilnahme. Diese umfasst Anwesenheit und enthält Ausarbeitung, Vortrag und Mitarbeit|
|Arbeitsaufwand:||Präsenzzeit: 30 h |
Vor- und Nachbereitung: 90 h
Summe: 120 h