Abgeschlossene Studien- und Abschlussarbeiten

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The amount of data produced in urban areas is steadily increasing. This is due to the increasing capabilities of devices and the desire to provide citizen advanced services based on the analysis of such data. Data is transmitted from a producer or publisher to a gateway access node, where it is further processed by in-network processing topologies to extract information and act in a timely manner. Contrary to stationary sensors, today’s data producers are highly mobile - examples include mobile phones and cars. These two sources of data will be the primary focus of this thesis. With a variety of highly mobile data publishers and different kinds of data, the question arises which communication patterns should be used to transfer the data to gateway nodes. This becomes especially relevant when publishers do not have an a-priori knowledge of subscribers and messages have different priorities.

30.11.2017

Intelligenter Browser für Process Mining

Bachelorarbeit

Abgeschlossen


Aus aufgezeichneten Eventlogs aus IT-Systemen und Maschinen können mittels Process Mining interessante Erkenntnisse extrahiert werden. Doch die Menge der gesammelten Daten kann mittels aktueller Verfahren nicht ohne Unterstützung analysiert werden, der Benutzer wird schlicht überfordert. Aktuelle Tools zeigen alle Daten auf einmal an, ohne sie systematisch oder intelligent filterbar zu machen. So ist das Finden von Auffälligkeiten und Schwachstellen schwierig.

31.10.2017

Scheduling Strategies for Apache Storm

Masterarbeit

Abgeschlossen


Data Stream Processing (DSP) systems have emerged as a way for the timely processing of real-time data generated by a variety of sources. Continuous streams of data from these sources are passed through different operators, each of which performs some computations on the data. The operators are chained and together form the overall logic of a stream processing application.
With new concepts such as In-network processing or edge computing, more and more devices become available to process data in the core network or at the extreme edge of the network, rather than in distant cloud computing architectures. Given this scenario, the question arises where to place and schedule operators. Strategies for placement and scheduling can optimize for different metrics (e.g. latency, resource utilization, user-defined QoS etc.). Furthermore, the problem is NP-hard, so efficient heuristics are needed to solve it in reasonable time.
This thesis examines the problem using Apache Storm as a DSP. For this system, several schedulers have been proposed in literature, however, they each employ a different approach and have a different focus for optimization. This makes it very hard to compare them and identify means to efficiently solve the placement problem.

We are currently in a smart-phone era. Mobile devices are gaining more popular than the exis- ting traditional computers. As the growth of technology increases, the possibility of increasing risks are higher. The risk of possible attacks for a mobile device are increasing and could be with physical access and remote access. Even though we do not have a major attack on mobile devices in past, there are some attacks which happened such as by sharing the non-signed and non-verified downloaded executable files to one another [MSCU2011]. Mobile security is one of the most important and key element in today’s world. Security and privacy-related are most important topics in such mobile devices scenarios. The possible factors of mobile attacks are less, because of less heterogeneity. To understand the heterogeneity and homogeneity with re- spect to mobile devices, consider a smart device which is manufactured by different companies with different operating system (handset manufacturers). For example, if we consider a black- berry or an apple which manufactures its own hardware and software (Operating System). In this scenario, the security features of the hardware is tightly coupled with the software they designed. So, the overall security outcome of such scenario is much better. The smart phone OS makers reluctant to give access to such hardware security features. But, even if the OS makers are willing to share such information via their customised APIs, the application developers or other parties are forced to fully trust the smart phone OS makers hardware based security API functions. Also, the companies such as apple are not sharing the information or APIs to access secure isolated environments. When comes to homogeneity, Even though the companies such as Motorola, LG, Samsung are bound in using the standard open platform Android, they are en- ding up manufacturing their own custom hardware specifications and custom software designs. This leads in implementing custom and buggy security properties as there is no standardization. Again in this case, application developers are forced to trust the modified OS and to fully trust the security based API functions if available. 

30.09.2017

V-Storage: A Virtual Storage Framework for Android

Bachelorarbeit

Abgeschlossen


Mobile devices such as smartphones today feature a variety of different apps, each one serving one particular purpose. Data captured or sent by those apps is usually stored at a distant server, i.e., in the cloud, but in any case at a location predetermined by that particular application.
Also, many users use different apps that serve the same or a similar purpose. The existing app landscape therefore hinders sharing data between different applications.
More importantly, the way these apps store and access data is completely decoupled to how the data is acutally used, what the current usage context and the user's intention is. In this thesis, we will provide a framework that abstracts from concrete storage locations and decides where to best place the data based on these factors. Furthermore, the emerging concept of Edge Computing provides an opportunity to place data close to the source, as to save latency and bandwidth in the core network.

25.09.2017

Business Rule Framework for Spark Streaming

Masterarbeit

Abgeschlossen


Smartphones have become the information hub for people and organizations.  In order to enhance the usability of smartphones, so-called mobile apps are available in app stores for download. Many of these apps are useful for our daily life. However, the current app stores do not provide means to support users in distinguishing “good” (trusted) apps from the “bad” (untrusted) ones considering security & privacy related factors. In this thesis, a system architecture is proposed to automate the trustworthiness assessment of mobile apps from an end-user perspective. We also plan to develop a solution to realize the system that calculates and visualizes the trust score of mobile apps.  

Die Analyse von Geschäftsprozessen mittels Process-Mining ermöglicht eine objektive Sicht auf einen Prozess durch Ermittlung des IST-Zustands auf Basis von Ereignis-Logs. Üblicher-weise werden zur Visualisierung Graphen oder Petri-Netze verwendet, der die tatsächlich ausgeführten Ereignisse und Abläufe repräsentiert. Oft ist das Ziel einer Prozessanalyse das Finden von Schwachstellen im Prozess (bspw. Schleifen in der Ausführung) und das Optimie-ren von Ausführungsvarianten (bspw. Reduktion der Prozessschritte).

Anpassungen am Prozessgraphen oder –modell werden heute durch Prozessexperten manuell vorgeschlagen und implementiert. Dies ist ein zeitaufwendiger und schwieriger Arbeitsschritt, da IST-Prozessgraphen selbst in kleinen und mittelgroßen Unternehmen sehr komplex werden können. Die Prozessgraphen können daher aktuell nur begrenzt für die Optimierung des be-trachteten Prozesses herangezogen werden.

Das Straßennetz ist das Kernelement für den Personen- und Güterverkehr innerhalb einer Stadt. In dem Netz sind tausende Sensoren verbaut um Fahrzeuge zu erkennen und um Fahrzeugströme optimal zu steuern. Besonders an Kreuzungen treten Engpässe auf, die durch Forschung an kooperativen Systeme und insbesondere Car-to-Car und Car-to-Infrastructure Technologien künftig verringert werden sollen. Hierbei spielen Internet of Things Ansätze eine große Rolle. Diese Arbeit nutzt Technologien des Internet of Things um Verkehrsinfrastruktur-Sensor- und -Signaldaten zu extrahieren, anzureichern und zu analysieren um sie dritten Anwendungen zur Verfügung zu stellen.

Diese Thesis adaptiert eine Belastungsmetrik (Degree of Saturation) des australischen SCATS auf ein reales deutsches Straßennetz. Hierbei müssen Lösungen für die Unterschiede zwischen australischen und deutschen Verkehrsnetzen erarbeitet und mit den Imperfektionen eines realen Verkehrsnetzes umgegangen werden.


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Forschungsgebiete

CASED
CRISP
CROSSING
CYSEC
Datenbanken und Verteilte Systeme
Embedded Sensing Systems
Graphisch-Interaktive Systeme
Information Systems
Knowledge Engineering
Knowledge Mining and Assessment
NICER
Peer-to-Peer Netzwerke
privacy-trust
RBG
Security, Usability and Society
Telecooperation
Ubiquitous Knowledge Processing
Zuverlässige Eingebettete Softwaresysteme

Forschungsteilgebiete

- ALW - Area Ambient Learning & Knowledge Work
- ALW: Algorithm Animation
- ALW: Digital Lecture Hall (DLH)
- ALW: Learning Strategies
- MDI - Area Model Driven Interaction
- NDS - Former Area Networks and Distributed Systems
- NDS: FormerProjects
- P2P - Area Peer-to-Peer Systems
- P2P: IPTV2.0
- P2P: Online social networks
- P2P: QuaP2P (jointly with SCS)
- SCS (Smart Civil Security)
- SE - Area Smart Environments
- SE: Mundo
- SE: MundoCore
- SE: Service Composition
- SE: Talking Assistant
- SI - Area Smart Interaction
- SI : Augur (finished)
- SPIN: Smart Protection in Infrastructures and Networks
- SSI - Area Secure Smart Infrastructures
- SST - Area Smart Security and Trust
- SST: CASED
- SST: Past Projects
- SUN - Smart Urban Networks
- TI - Area Tangible Interaction
- TI: Interactive Surfaces
- TNT - Area Talk and Touch Interaction
- TNT: Mundo Speech API
- TnT: UI Blind Meeting
DVS/Peer-to-Peer
E-Learning
Mobile Networking
Peer-to-Peer Networking
S1
Secure Services
Secure Things
Security
Security, Usability and Society
Ubiquitous Computing
UKP_p_SIR3
UKP_p_TextAsProcess
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