Laufende Studien- und Abschlussarbeiten

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Aus aufgezeichneten Eventlogs aus IT-Systemen und Maschinen kann mittels Process Mining Discovery Algorithmen der tatsächliche IST-Ablauf visuell rekonstruiert werden. Hieraus lassen sich interessante Erkenntnisse gewinnen, z.B. wie sich die Durchlaufzeit bestimmter Aktivitäten verhält oder ob alle notwendigen Aktivitäten überhaupt ausgeführt werden. Durch die Zunahme an Komplexität von Geschäftsprozessen werden rekonstruierte Prozessmodelle immer unübersichtlicher und lassen sich somit nur schwer analysieren. Aktuelle Process Mining Tools zeigen alle Daten auf einmal an, sodass ein Analyst nur mit Schwierigkeiten die wichtigen Erkenntnisse extrahieren kann.

Checking certain business rules in process models (e.g. petri-nets, BPMN or flow graphs) is usually done using a model checker or an automata. Increasing models and the increasing amount of rules lead to long computation times. The Taint Flow Analysis operates on graphs to determine certain flows (source to sink). With a neat conversion of rules we can check business rules on flow graphs very efficiently. However, the current approach is limited.

The latest trend in computing world is the cloud computing which is Internet-based computing that provides shared computer processing resources and data to computers and other devices on demand. There are numbers of cloud providers that provide different services, e.g. Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), to users. Users need to select the most trustworthy service provider that they can totally rely upon to fulfil their demands. For this purpose, trust calculation plays an important role. Because the limited Web interfaces do not allow users to identify the trustworthiness of service providers like typical face-to-face interaction. Users can find the trustworthiness of a service provider in cloud reputation services, e.g. TaaS4Cloud.  The functionality of this web service can be enhanced by users’ ratings and recommendations to make it more user-centric. So that users can select the appropriate provider they need. In this case, trustworthiness of the users should also be considered to get more dependable recommendations. We can fulfil these requirements of users to select the most trustworthy providers by implementing a trust-oriented recommender system for cloud reputation services.


Intelligenter Browser für Process Mining


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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.

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. 

Ziel dieser Bachelorarbeit ist ein Framework, zur Granularitätssteuerung von personally identifiable information (PII) anhand von Preisfunktionen. Dieses Framework soll als Schicht zwischen Benutzer und Service Provider genutzt werden und eine Granularisierung der gegebenen PII anhand von gegebenen Preisfunktionen ermöglichen. 


Trust in Collaborative Intrusion Detection


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Anomaly Detection in Business Processes Using LSTMs


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Datenbanken und Verteilte Systeme
Embedded Sensing Systems
Graphisch-Interaktive Systeme
Information Systems
Knowledge Engineering
Knowledge Mining and Assessment
Peer-to-Peer Netzwerke
Security, Usability and Society
Ubiquitous Knowledge Processing
Zuverlässige Eingebettete Softwaresysteme


- 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: 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
Mobile Networking
Peer-to-Peer Networking
Secure Services
Secure Things
Security, Usability and Society
Ubiquitous Computing
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