TY  - CHAP
A1  - Gronau, Norbert
A1  - Grum, Marcus
A1  - Bender, Benedict
T1  - Determining the optimal level of autonomy in cyber-physical production systems
T2  - IEEE 14th International Conference on Industrial Informatics (INDIN)
N2  - Traditional production systems are enhanced by cyber-physical systems (CPS) and Internet of Things. A kind of next generation systems, those cyber-physical production systems (CPPS) are able to raise the level of autonomy of its production components. To find the optimal degree of autonomy in a given context, a research approach is formulated using a simulation concept. Based on requirements and assumptions, a cyber-physical market is modeled and qualitative hypotheses are formulated, which will be verified with the help of the CPPS of a hybrid simulation environment.
KW  - cyber-physical systems
KW  - hybrid simulation
KW  - Internet of Things
KW  - manufacturing systems
KW  - production engineering computing
KW  - cyber-physical production systems
Y1  - 2017
U6  - https://doi.org/10.1109/INDIN.2016.7819367
SP  - 1293
EP  - 1299
PB  - IEEE
CY  - New York
ER  - 
TY  - CHAP
A1  - Bender, Benedict
A1  - Grum, Marcus
T1  - Entwicklung eines Architekturkonzepts zum flexiblen Einsatz von Analytics
T2  - Proceedings INFORMATIK - Jahrestagung der Gesellschaft für Informatik e.V. ; Lecture Notes in Informatics (LNI)
N2  - Die optimale Dimensionierung von IT-Hardware stellt Entscheider aufgrund der stetigen Weiterentwicklung zunehmend vor Herausforderungen. Dies gilt im Speziellen auch für Analytics-Infrastrukturen, die zunehmend auch neue Software zur Analyse von Daten einsetzen, welche in den Ressourcenanforderungen stark variieren. Damit eine flexible und gleichzeitig effiziente Gestaltung von Analytics-Infrastrukturen erreicht werden kann, wird ein dynamisch arbeitendes Architekturkonzept vorgeschlagen, das Aufgaben auf Basis einer systemspezifischen Entscheidungsmaxime mit Hilfe einer Eskalationsmatrix verteilt und hierfür Aufgabencharakteristiken sowie verfügbare Hardwareausstattungen entsprechend ihrer Auslastung berücksichtigt.
KW  - Analytics
KW  - Architekturkonzept
KW  - Cyber-Phsysische Systeme
KW  - Cloud
KW  - Internet of Things
Y1  - 2016
UR  - https://dl.gi.de/handle/20.500.12116/1189
IS  - P259
SP  - 815
EP  - 824
PB  - Gesellschaft für Informatik e.V.
CY  - Bonn
ER  - 
TY  - CHAP
A1  - Glaschke, Christian
A1  - Gronau, Norbert
A1  - Bender, Benedict
T1  - Cross-System Process Mining using RFID Technology
T2  - Proceedings of the Sixth International Symposium on Business Modeling and Software Design - BMSD
N2  - In times of digitalization, the collection and modeling of business processes is still a challenge for companies. The demand for trustworthy process models that reflect the actual execution steps therefore increases. The respective kinds of processes significantly determine both, business process analysis and the conception of future target processes and they are the starting point for any kind of change initiatives. Existing approaches to model as-is processes, like process mining, are exclusively focused on reconstruction. Therefore, transactional protocols and limited data from a single application system are used. Heterogeneous application landscapes and business processes that are executed across multiple application systems, on the contrary, are one of the main challenges in process mining research. Using RFID technology is hence one approach to close the existing gap between different application systems. This paper focuses on methods for data collection from real world objects via RFID technology and possible combinations with application data (process mining) in order to realize a cross system mining approach.
KW  - Process Mining
KW  - RFID
KW  - Production
KW  - Cross-System
Y1  - 2016
SN  - 978-989-758-190-8
U6  - https://doi.org/10.5220/0006223501790186
SP  - 179
EP  - 186
PB  - SCITEPRESS - Science and Technology Publications
CY  - Setúbal
ER  - 
TY  - CHAP
A1  - Bender, Benedict
A1  - Fabian, Benjamin
A1  - Lessmann, Stefan
A1  - Haupt, Johannes
T1  - E-Mail Tracking
BT  - status quo and novel countermeasures
T2  - Proceedings of the 37th International Conference on Information Systems (ICIS)
N2  - E-mail advertisement, as one instrument in the marketing mix, allows companies to collect fine-grained behavioural data about individual users’ e-mail reading habits realised through sophisticated tracking mechanisms. Such tracking can be harmful for user privacy and security. This problem is especially severe since e-mail tracking techniques gather data without user consent. Striving to increase privacy and security in e-mail communication, the paper makes three contributions. First, a large database of newsletter e-mails is developed. This data facilitates investigating the prevalence of e- mail tracking among 300 global enterprises from Germany, the United Kingdom and the United States. Second, countermeasures are developed for automatically identifying and blocking e-mail tracking mechanisms without impeding the user experience. The approach consists of identifying important tracking descriptors and creating a neural network-based detection model. Last, the effectiveness of the proposed approach is established by means of empirical experimentation. The results suggest a classification accuracy of 99.99%.
KW  - E-Mail Tracking
KW  - Countermeasures
KW  - Privacy
KW  - Security
KW  - Machine Learning
Y1  - 2016
UR  - https://aisel.aisnet.org/icis2016/ISSecurity/Presentations/13/
ER  -